Data Entry Jobs - Doha Qatar

Data Governance, Privacy & GRC Consultant Location: Doha, Qatar or Dubai, UAE Employment Type: Full-time (On-site / Client Site) Company: Command Post About Command Post Command Post is a leading cybersecurity, AI assurance, governance, risk, compliance (GRC), privacy, and data governance consulting and technology company serving organizations across the Middle East. As part of our continued growth, we are expanding our Data Governance and GRC practice and are looking for experienced professionals to join our team in Qatar and the UAE. Open Positions We are hiring across multiple experience levels, including:Data Governance Lead Senior Data Governance Consultant Data Governance Consultant GRC / Compliance Lead Privacy Consultant Data Governance Analyst Data Steward Role Overview The successful candidate will support the design, implementation, and continuous improvement of enterprise governance, privacy, compliance, and risk management programs. You will work closely with business and technical stakeholders to establish governance frameworks, improve data quality, ensure regulatory compliance, and strengthen organizational controls. Key Responsibilities Data Governance Design and implement enterprise data governance frameworks. Establish governance structures, decision rights, roles, and responsibilities. Define Data Owner, Data Steward, and Data Custodian operating models. Develop governance policies, standards, procedures, and operating models. Build and maintain business glossaries, metadata repositories, data dictionaries, and data catalogues. Define data quality rules, KPIs, ownership, and issue management processes. Conduct data governance maturity assessments and develop improvement roadmaps. Facilitate workshops with business and technology stakeholders. Support Data Governance Councils and governance working groups. Develop governance dashboards, KPIs, and executive reports. Data Lineage & Data Flow Management Document end-to-end data flows across applications, databases, interfaces, and third-party platforms. Develop enterprise data lineage models. Identify data sources, transformations, integrations, storage locations, and downstream consumers. Validate data flows with business users, architects, engineers, and application owners. Identify governance gaps, duplicate data, uncontrolled transfers, and ownership issues. Support critical data element identification and lifecycle management. Contribute to data migration, integration, and transformation initiatives. Governance, Risk & Compliance (GRC) Design and implement enterprise GRC frameworks. Perform governance, risk, and compliance assessments. Maintain risk registers, compliance registers, control libraries, and evidence repositories. Develop policies, procedures, standards, and control documentation. Support ISO certifications, audits, and regulatory assessments. Track remediation plans, risk treatment actions, and compliance status. Support information security, privacy, AI governance, and data governance compliance initiatives. Privacy Management Design and support enterprise privacy programs. Maintain Records of Processing Activities (RoPA). Conduct Data Protection Impact Assessments (DPIAs). Support privacy risk assessments. Manage Data Subject Access Request (DSAR) processes. Support consent, retention, deletion, breach management, and third-party privacy processes. Map personal data across business units and applications. Support Privacy by Design implementation. Maintain privacy documentation and compliance evidence. Data Discovery & Privacy Technology Implement and support data discovery and classification platforms. Identify sensitive, regulated, and business-critical information. Validate classifications, ownership, retention, and processing purposes. Configure scanning policies, taxonomies, workflows, and connectors. Integrate discovery outputs into governance and compliance processes. Experience with Fides is an advantage. AI Governance & Assurance Support AI governance frameworks and operating models. Build AI inventories and AI risk classification processes. Conduct AI risk and impact assessments. Support ISO/IEC 42001 implementation. Evaluate AI systems for governance, security, privacy, transparency, accountability, and operational risk. Integrate AI governance into enterprise GRC and cybersecurity programs. Experience with Qatar Central Bank AI requirements or similar regional AI regulations is desirable. Standards & Regulatory Experience Experience with one or more of the following is preferred:ISO/IEC 27001ISO/IEC 42001Information Security Management Systems (ISMS) AI Management Systems (AIMS) Privacy and Data Protection Regulations Qatar Data Protection Law UAE Data Protection Law Qatar Central Bank AI Requirements Risk & Control Frameworks Data Governance Frameworks Internal Audit & Compliance Technology Experience Experience with one or more of the following platforms is advantageous:One Trust CISO Assistant Fides Collibra Informatica Microsoft Purview Big IDData Discovery Platforms Data Catalog & Metadata Management Tools GRC Platforms Privacy Management Solutions Compliance & Evidence Management Platforms Required Skills & Experience Experience in Data Governance, Privacy, GRC, Compliance, or Data Management. Strong understanding of governance frameworks, policies, and controls. Experience conducting risk assessments and governance workshops. Excellent stakeholder management and communication skills. Strong analytical and documentation abilities. Customer-facing consulting experience. Ability to work independently and collaboratively. Willingness to work on-site in Doha or Dubai. For Lead Positions Experience leading governance and compliance programs. Managing project teams and stakeholder engagement. Designing governance operating models. Delivering assessments, roadmaps, and implementation projects. Managing budgets, risks, and project delivery. Mentoring junior consultants and supporting business development. For Consultant / Analyst Positions Experience supporting governance initiatives. Documentation and policy development. Risk and compliance tracking. Privacy and data governance support. Reporting and stakeholder coordination. Preferred Skills Data Quality Management Master Data Management (MDM) Cloud Data Governance Regulatory Compliance Audit & Certification Readiness AI Governance & Model Risk Privacy Engineering Data Classification Information Lifecycle Management Data Architecture Data Engineering Systems Integration Cybersecurity Governance Middle East consulting experience Education & Certifications Degree Bachelor's or Master's degree in Information Technology, Computer Science, Data Management, Information Security, Business, or a related discipline. Preferred Certifications DAMA Certified Data Management Professional (CDMP) ISO/IEC 27001 Lead Implementer or Lead Auditor ISO/IEC 42001 Lead Implementer or Lead Auditor CIPP, CIPM, CIPT, or equivalent privacy certifications CRISC, CISA, CISSP, or similar GRC certifications One Trust Certifications Collibra Certifications Microsoft Purview Certifications Informatica Certifications Project Management (PMP, PRINCE2) Business Analysis Certifications Relevant practical consulting and implementation experience will be considered alongside professional certifications. Candidate Profile We are looking for professionals who are:Detail-oriented and highly organized. Strong communicators with excellent stakeholder management skills. Passionate about governance, privacy, AI governance, and compliance. Comfortable working with both business and technical teams. Able to translate regulatory requirements into practical governance solutions. Committed to delivering high-quality consulting services in customer-facing environments. Please submit your updated CV highlighting your experience in:Data Governance Privacy Management GRC & Compliance Data Lineage & Data Flow Mapping Data Discovery & Classification ISO/IEC 27001ISO/IEC 42001AI Governance & Assurance Governance, Privacy, Compliance, and Data Management Technologies

Position Summary:The Lead Data Engineer is responsible for leading the design, development, implementation, and optimization of scalable cloud-based data platforms and engineering solutions that enable analytics, business intelligence, and data-driven decision-making across Group Digital. The role provides technical leadership, establishes engineering best practices, ensures the delivery of secure and high-performance data solutions, and supports the continuous evolution of the organization’s data ecosystem.<br>Key Responsibilities and Accountabilities:Lead the design, development, implementation, and optimization of scalable cloud-based data platforms, data lakes, and data pipelines supporting Group Digital initiatives. Design, build, and maintain robust ETL/ELT pipelines using SQL, Python, and modern cloud technologies to integrate data from multiple internal and external sources. Develop and optimize data models, storage architectures, and processing frameworks to ensure high performance, scalability, reliability, and cost efficiency. Establish and enforce data engineering standards, coding best practices, documentation, and governance across the data engineering function. Collaborate with Business Intelligence, Product, Technology, Commercial, Marketing, and Content teams to translate business requirements into scalable technical solutions. Ensure data quality, integrity, security, and compliance through monitoring, validation, and governance processes. Support the development of analytics, reporting, dashboards, and self-service BI capabilities by delivering reliable and trusted datasets. Optimize cloud infrastructure, database performance, and processing workloads to improve system availability and operational efficiency. Troubleshoot and resolve complex data platform issues, ensuring minimal disruption to business operations. Mentor and provide technical guidance to Data Engineers, promoting knowledge sharing and continuous capability development. Provide technical leadership across the Data Engineering function by driving engineering best practices, mentoring engineers, and guiding technical decisions across Group Digital. Work closely with cross-functional stakeholders, vendors, and technology partners to deliver data engineering initiatives aligned with business priorities. Contribute to Agile delivery by participating in sprint planning, backlog refinement, code reviews, testing, deployment, and continuous improvement activities. Ensure adherence to enterprise data governance, security, architecture, and compliance standards.<br>Job Requirements and Qualifications:Education: Bachelor’s degree in computer science, Information Technology, Software Engineering, Data Engineering, or a related field. A master’s degree or relevant cloud certifications (e.g., Google Cloud Professional Data Engineer, Google Cloud Professional Cloud Architect) is an advantage. Experience: Minimum 7+ years of progressive experience in Data Engineering, Data Platform Development, or related disciplines. Proven experience designing and implementing enterprise-scale data platforms and cloud-native data solutions. Experience leading technical initiatives and mentoring engineering teams. Hands-on experience with Google Cloud Platform (GCP) or equivalent cloud technologies.

Job Description<br><br>Strong experience in data analysis, data engineering, or AI development (Microsoft Copilot, Google Gemini Enterprise) Proficiency in programming languages such as Python and SQL. Experience with machine learning frameworks Knowledge of data visualization and BI tools Understanding of databases, data warehouses, and cloud data platforms Strong analytical and problem-solving skills Good communication and documentation abilities<br><br>Responsibilities<br><br>Design, develop, and maintain data pipelines, databases, and data platforms Collect, clean, and transform structured and unstructured data Build, train, test, and deploy AI / machine learning models Develop dashboards, reports, and data insights for business users Integrate AI solutions with business applications and systems Ensure data quality, governance, security, and privacy compliance Monitor and optimize data and AI model performance Collaborate with business, IT, and analytics teams to translate needs into solutions Document data models, pipelines, and AI solutions<br><br>Qualifications<br><br>Bachelor’s degree3-6 years of experience Experience with cloud platforms (AWS, Azure, GCP)

Black & Grey HR is recruiting for an established technology solutions and services provider in Doha, Qatar. Our client is seeking an experienced Security Operations Officer – Data Security Specialist responsible for executing and enhancing security operations, monitoring and responding to threats with a focus on mega sports events and non-event periods. Collaborate across teams to implement effective security measures for information systems.<br>Key Responsibilities Data Security Engineering Design and implement data protection controls across enterprise, cloud environments and Artificial Intelligence Solutions. Deploy and manage solutions such as Data Loss Prevention (DLP), data masking, and tokenization. Collaborate with application and infrastructure teams to embed security into data lifecycle management. Implement and manage data discovery and classification tools to identify, categorize, and label sensitive data across the organization. Continuously monitor data security posture and produce regular compliance and risk reports. Assist the incident response team in investigating and responding to data security incidents, including insider threats and breaches.<br>Cloud Data Security Implement and manage data protection controls in GCP and Azure. Secure databases and data lakes. Configure encryption at rest, in transit, and in use, with BYOK strategies. Deploy cloud-native data discovery and classification solutions. Manage secrets management and ensure secure access to data storage systems. Implement controls for AI data governance.<br>Cryptography Define and enforce cryptographic practices and key management standards. Manage enterprise encryption practices for data at rest, in transit, and in use. Ensure compliance with organizational and industry cryptographic standards.<br>Data Privacy Ensure compliance with privacy regulations (GDPR, HIPAA, PDPPL). Embed privacy-by-design principles and requirements into technical controls. Drive data classification and governance programs to safeguard personal and sensitive information.<br>Database Security Secure structured and unstructured data repositories, including relational and NoSQL databases. Implement database activity monitoring (DAM) and user access controls. Perform regular security reviews and hardening of database systems.<br>Collaboration & Governance Collaborate with other stakeholders on data protection strategies. Ensure compliance with Qatar’s NCSA framework and international standards. Conduct data security assessments for vendors and third-party integrations. Review and approve data sharing agreements. Define and track data security KPIs and metrics. Maintain data security dashboards for continuous monitoring. Stay current with emerging threats, technologies, and industry best practices.<br>Requirements8+ years of experience in information security with a focus on data protection, cryptography, and database security. Bilingual (Arabic Speaker) Preferred. Hands-on experience with cloud platforms, especially GCP and Azure. Strong understanding of encryption standards, cryptographic protocols, and key management processes. Practical experience with secrets management (Hashi Corp Vault, AWS Secrets Manager, Azure Key Vault, GCP Secret Manager). Proven expertise in cloud-native data protection across multi-cloud environments. Experience implementing data masking, tokenization, and anonymization techniques. Bachelor’s degree in computer science, Information Security, or related field. Professional certifications such as CISSP, CCSP, CDPSE, or CCSK. Cloud security certifications (GCP, Azure, or AWS Security Specialty) preferred.<br>Required Skillsets Hands-on experience with DLP solutions (Forcepoint, Microsoft Purview, Google Cloud DLP). Implementation of data anonymization, pseudonymization, and masking techniques. Configuration and monitoring of DAM solutions (Imperva, IBM Guardium). Experience with data discovery and classification tools (Forcepoint, Microsoft Purview). Strong knowledge of cryptographic and key management systems (KMS, GCP Cloud KMS, Azure Key Vault). Securing relational, NoSQL, and data lake environments. Performing database vulnerability assessments and security audits. Working knowledge of secret management solutions and integration with CI/CD pipelines.

The Tax Compliance Risk Data & Modelling Expert oversees end-to-end processing of tax data assets, analyzes cross-system tax information, and develops analytical and predictive models to support compliance risk assessment and strategic decision-making. The role coordinates with IT on analytical tools, reviews international and exchanged tax data, and advises on data governance practices to ensure quality, consistency, and secure access for Tax departments. Tax Data Assets & Governance Oversee the end-to-end cycle of tax data, including acquisition from internal and external systems, validation, cleansing, storage, and evaluation. Develop and Monitor data governance practices to Ensure tax data quality, consistency, security, and controlled access, including maintenance of central data dictionaries and metadata. Risk Data Analysis & Modelling Analyze tax data using statistical and exploratory techniques to Identify patterns relevant to compliance risk and operational performance. Develop and Review predictive and analytical models that Support risk-based assessment, audit targeting, and monitoring of tax gaps. Dashboards, Analytics & Strategic Insights Develop advanced dashboards and analytical views to Support operational monitoring and strategic planning across TAX Authority. Prepare structured analytical outputs and reports for senior management, including key indicators, trends, and sectoral insights. Stakeholder Engagement & Requirements Coordinate regular meetings with relevant departments to Assess data and analytics needs, Identify gaps, and Align data sources and structures with operational requirements. Prepare and Review lists of missing or incomplete tax data needed to Support official tasks and risk analysis. Tools, Systems & International Data Coordinate with IT to Develop and Enhance analytical tools, including predictive analytics and automated reporting systems that Support tax risk evaluation and decision-making. Analyze data received through tax information exchange mechanisms and Evaluate its relevance for risk analysis and compliance activities. Support to Internal & External Requests Advise regulatory and operational units on the use of data and analytical outputs in urgent or high-priority cases requiring rapid information. Review and Prepare analytical inputs for requests from International Cooperation department related to tax data, in line with applicable frameworks. Preferred Qualifications & Experience Bachelor’s degree in Data Science, Statistics, Economics, Computer Science, or related field. Master’s degree in a related field is preferred. Relevant professional certifications are an advantage. 16+ years of relevant experience in data analytics, statistical modelling, or risk analytics in tax administration, government, or a related financial/compliance environment. Demonstrated knowledge of tax data structures, analytical tools, and data governance concepts. Strong data analysis and modelling skills using analytical and BI tools. Ability to translate complex data into clear insights and decision-support outputs. Effective coordination and communication with technical and non-technical stakeholders. Attention to data quality, structure, and security.

The Tax Compliance Risk Data & Modelling Expert oversees end-to-end processing of tax data assets, analyzes cross-system tax information, and develops analytical and predictive models to support compliance risk assessment and strategic decision-making. The role coordinates with IT on analytical tools, reviews international and exchanged tax data, and advises on data governance practices to ensure quality, consistency, and secure access for Tax departments. Tax Data Assets & Governance Oversee the end-to-end cycle of tax data, including acquisition from internal and external systems, validation, cleansing, storage, and evaluation. Develop and Monitor data governance practices to Ensure tax data quality, consistency, security, and controlled access, including maintenance of central data dictionaries and metadata. Risk Data Analysis & Modelling Analyze tax data using statistical and exploratory techniques to Identify patterns relevant to compliance risk and operational performance. Develop and Review predictive and analytical models that Support risk-based assessment, audit targeting, and monitoring of tax gaps. Dashboards, Analytics & Strategic Insights Develop advanced dashboards and analytical views to Support operational monitoring and strategic planning across TAX Authority. Prepare structured analytical outputs and reports for senior management, including key indicators, trends, and sectoral insights. Stakeholder Engagement & Requirements Coordinate regular meetings with relevant departments to Assess data and analytics needs, Identify gaps, and Align data sources and structures with operational requirements. Prepare and Review lists of missing or incomplete tax data needed to Support official tasks and risk analysis. Tools, Systems & International Data Coordinate with IT to Develop and Enhance analytical tools, including predictive analytics and automated reporting systems that Support tax risk evaluation and decision-making. Analyze data received through tax information exchange mechanisms and Evaluate its relevance for risk analysis and compliance activities. Support to Internal & External Requests Advise regulatory and operational units on the use of data and analytical outputs in urgent or high-priority cases requiring rapid information. Review and Prepare analytical inputs for requests from International Cooperation department related to tax data, in line with applicable frameworks. Preferred Qualifications & Experience Bachelor’s degree in Data Science, Statistics, Economics, Computer Science, or related field. Master’s degree in a related field is preferred. Relevant professional certifications are an advantage. 16+ years of relevant experience in data analytics, statistical modelling, or risk analytics in tax administration, government, or a related financial/compliance environment. Demonstrated knowledge of tax data structures, analytical tools, and data governance concepts. Strong data analysis and modelling skills using analytical and BI tools. Ability to translate complex data into clear insights and decision-support outputs. Effective coordination and communication with technical and non-technical stakeholders. Attention to data quality, structure, and security.

ROLES & RESPONSIBILITIES :<br>Data Authority & Accountability Define and enforce data ownership and accountability models Ensure all KPIs and AI features have accountable data owners Act as the final authority for data used in Observatory decisions<br>Data Maturity Governance for Decision Confidence Govern maturity of data supporting KPI interpretation and performance monitoring Assess data stability, consistency, and historical integrity Communicate data confidence levels and limitations to decision-makers<br>Data Governance for AI & Decision Intelligence Govern data suitability for AI training and inference Assess risks such as bias, leakage, and feature instability Support AI accreditation decisions with data authority insights<br>SKILLS & COMPETENCIES :<br>Bachelor’s degree in Information Systems, Data Management, or related field DAMA/CDMP or equivalent certifications preferred

Role :This role is responsible for leading and overseeing the organization's Data Governance function, ensuring that data is trusted, well-defined, protected, and effectively utilized to support business decision-making, AI initiatives, and regulatory compliance. The role acts as the key link between business units, IT, BI, Risk, Privacy, and Compliance functions to establish and sustain a robust data-driven culture. <br>This position owns the Data Governance program end-to-end, including thedevelopment and implementation of governance frameworks, policies, standards, and operating models that ensure data integrity, quality, security, accessibility, and compliance with applicable regulations and industry standards. <br>The role is accountable for the effective management of data quality, metadata, master data, stewardship, and governance processes across the organization. Additionally, the role drives Data Governance projects and strategic initiatives, overseeing execution through the Data Governance Council, coordinating cross-functional stakeholders, managing risks and dependencies, monitoring progress, and ensuring the timely delivery of governance objectives aligned with business priorities. The role also contributes to the development and execution of data and AI governance strategies, fostering innovation, operational excellence, and alignment with the organization's strategic goals.<br>About the Business Unit:AI & Data Governance team is responsible for developing and implementing data governance frameworks and AI strategies to ensure data integrity, security, compliance, and to drive innovation and operational excellence within Ooredoo. Additionally, the team manages AI projects and proof of concepts, tracks data initiatives, and coordinates with cross functional teams to ensure timely delivery and value realization.<br>Minimum Experience, Essential Knowledge & Skills:10 years' experience in a similar role. Experience in Data Management, Governance, Quality and Strategy. Strong understanding of Data governance operating models and best practices. Data privacy laws and compliance frameworks. AI governance, ethical AI principles, and responsible data usage.<br>Minimum Qualifications:Bachelor's Degree in Business Administration or Engineering or Project Management.

Role Objective <br>The incumbent will perform activities pertaining to Data Privacy across Doha Bank, in line with policies, procedures and applicable Data Privacy laws and regulations. The incumbent will support in development and implementation of the bank’s Data Privacy Program, ensure data compliance through relevant mechanism, and impart staff training in close coordination with the relevant stakeholders.<br>Detailed Roles and Responsibilities:<br>Perform all operational activities as assigned by the reporting authority, in compliance with local regulations, Doha Bank’s policies and units/departments approved policies and procedures. Support in development and implementation of the bank’s Data Privacy framework, and program in accordance with relevant Data Privacy laws and regulations. Work closely with the respective stakeholders to ensure compliance with applicable Data Privacy laws and regulations for the bank. Prepare Data Privacy policies, procedures & notices and perform annual review of these documents for their compliance to legal, regulatory and organizational updates. Work closely with the relevant stakeholders in implementation of the Data Privacy policies, procedures and notices across the Bank. Assist the Privacy Champions and IT Application Managers in maintenance of Record of Processing Activities and Data Flow Diagrams (DFDs). Perform Data Privacy Impact Assessment of the bank’s business process and IT applications processing personal data of the staff, customers, vendors, etc. Coordinate with relevant stakeholders to ensure all business processes adhere to internal Data Privacy policies and procedures. Coordinate with IT Application owners to ensure all IT Applications containing personal data adhere to internal Data Privacy policies and procedures.<br>Educational Qualifications and Experience: <br>University graduate with a degree in Computer Science, Computer Engineering, Information Security or any other related discipline.05-08 years of total experience in financial services/banking industry, entailing responsibilities pertaining to the specific area of discipline. Previous experience in Data Privacy /Data Protection or data compliance in financial services industry.

Role Purpose<br><br>The Data Quality Consultant helps clients understand, measure and improve the fitness of data for operational, analytical and public-service use. The role profiles data, defines quality dimensions and rules, establishes thresholds and monitoring, investigates root causes and supports sustainable remediation and issue-management processes.<br><br>The consultant works with Data Owners, Data Stewards, business experts, architects, engineers and system teams to ensure that quality expectations are tied to real business needs and authoritative reference sources. The role prepares evidence, recommendations and remediation plans, but client owners remain accountable for accepting quality risks and approving corrective actions. Effective delivery requires both analytical capability and facilitation skill so that technical findings become practical ownership, process and control improvements.<br><br>Key Responsibilities<br><br>Identify critical datasets, attributes, decisions and business processes requiring data-quality management. Profile data to identify completeness, validity, consistency, uniqueness, timeliness, accuracy and accessibility issues. Define data-quality rules, thresholds, reference sources, calculation logic and exception conditions with business stakeholders. Develop quality assessment plans, rule registers, scorecards, monitoring specifications and evidence requirements. Calculate and validate quality results and explain the implications for operational and analytical use. Maintain data-quality issue registers and support transparent prioritisation based on impact, urgency, frequency, sensitivity and complexity. Facilitate root-cause analysis across process, people, system, integration and data-design factors. Develop remediation plans with owners, target dates, dependencies, validation steps and closure evidence. Coordinate quality controls with metadata, master data, architecture, engineering, security and analytics teams. Define dashboards and reporting routines for ongoing monitoring and escalation. Validate remediation outcomes and distinguish corrected records from resolved root causes. Train client teams to maintain rules, interpret measures, investigate issues and govern exceptions.<br><br>Minimum Requirements<br><br>Education<br><br>Bachelor's degree in data science, statistics, computer science, information systems or a related field. An equivalent combination of relevant education and directly applicable consulting or implementation experience may be considered.<br><br>Professional Experience<br><br>Typically 4-8 years in data quality, data analysis, testing, governance or data engineering. Experience in data quality, data analysis, data governance, business intelligence or related data-management work. Practical experience profiling data and defining or testing quality rules and thresholds. Experience supporting root-cause analysis, remediation and quality monitoring. Experience explaining quantitative findings to business and technical stakeholders.<br><br>Technical and Domain Knowledge<br><br>Data-quality dimensions, rules, thresholds and measurement methods. Data profiling, anomaly detection and reference-data comparison. Issue prioritisation, root-cause analysis and remediation tracking. Quality scorecards, monitoring, dashboards and escalation. SQL and analytical techniques for validating data. Metadata, lineage, master data and architecture dependencies. Business-rule documentation and control evidence. Quality considerations for operational, analytical and shared data.<br><br>Core Competencies<br><br>Data profiling. Rule design. Root-cause analysis. SQL and analysis. Issue prioritization. Quality monitoring. Analytical rigour. Root-cause thinking. Evidence discipline. Continuous improvement. Facilitating rule-definition and root-cause workshops. Explaining calculations, evidence and limitations clearly. Writing precise rules, findings and remediation actions. Working constructively with data owners, stewards and technical teams. Challenging unsupported assumptions about data fitness. Prioritising issues based on business impact rather than volume alone. Transferring repeatable monitoring and investigation practices to clients.<br><br>Preferred Certifications<br><br>CDMP Associate or Practitioner, with Data Quality specialty preferred ISTQB CTFL where testing is material<br><br>Focus areas<br><br>Data profiling Rule design Root-cause analysis<br><br>Ready to apply for this role?<br><br>Apply for Data Quality Consultant

Hello!! Greetings from Linnk Group!! Job Title: Data Engineer???? Location: Doha, Qatar???? Experience: 5+ Years???? Employment Type: Yearly Renewable Contract----???? Candidate Preference:✅ Candidates currently based in Qatar only.✅ Arabic & European nationals only.<br>Job Overview We are looking for an experienced Data Engineer to design, build, and optimize scalable data pipelines and modern data platforms supporting analytics and AI initiatives.<br>Key Responsibilities Build and maintain ETL/ELT data pipelines. Develop solutions using Azure Data Factory, Synapse, and Databricks. Manage relational, NoSQL, and vector databases. Design data models and optimize SQL queries. Ensure data quality, governance, and pipeline performance. Collaborate with cross-functional teams to support AI and analytics projects.<br>Required Skills5+ years of Data Engineering experience. Strong Python and SQL skills. Hands-on experience with Azure Data Factory, Synapse, and Databricks. Experience with relational, NoSQL, and vector databases (Pinecone, Weaviate, etc.). Knowledge of ETL/ELT, data modelling, and schema design. Preferred Skills Experience with LLM data preparation, RAG, and semantic search. Knowledge of Azure Open AI or other Gen AI platforms. Familiarity with data governance and compliance.<br>If you are interested in for the role, please do share your CV to subin.pv@linnk.com<br>KR,

Job Description<br><br>Must have a production experience in building metadata driven ELT/ETL frameworks for data ingestion and processing. Must have a production experience working with Data lakes, ETL/ELT, Data warehousing using Azure ADLS Gen2, Databricks, Azure Data Factory, & Synapse Analytics Working knowledge stream processing pipelines and highly scalable big data stores using Spark, Azure Stream Analytics, Event Hubs, Azure Data Explorer etc. Experience with relational SQL, NoSQL databases, and data lakes: Azure SQL Database, Azure Data Lake. Experience with data management and data governance tools e.g. Azure Purview Experience with programming languages and scripting: Python, Scala, Java, bash, Azure CLI, Power Shell etc. Must have a strong understanding of CI/CD practices and technologies specifically Azure Dev Ops Must have substantial background in data extraction and transformation, developing data pipelines using MS SSIS and Azure Data Factory, Informatica IDMC. Strong understanding of business processes, requirements analysis, and collaboration with business system owners to design and build data products. Good to have. OCI data engineering experience. Experience with big data tools: Hadoop, Spark, Kafka, Storm, Hive, Hbase<br><br>Responsibilities<br><br>Create and maintain optimal and scalable data pipeline architecture. Assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources. Drive design, model, implement, and operate large, structured and unstructured datasets. Evaluate and implement efficient distributed storage and query techniques. Design and implement monitoring of data services platform. Design and implement Data Lakes and Data Warehouse solutions. Keeps track of industry best practices and trends and through acquired knowledge, takes advantage of process and system improvement opportunities. Develop and maintain technical documentation and operational procedures.<br><br>Qualifications<br><br>Bachelor's degree in fields like Computer Science, Computer Engineering, Business Analytics, or a related field. Certification: Azure certified data engineer8+ years hands-on ETL development experience,Data pipeline design & development,Data lakes & Warehouse project development experience, MS Azure Data Factory/SSIS. Azure Delta lake, Azure storage, Informatica IDMC. Azure certification Proven experience building, optimizing, and monitoring big data pipelines, architectures, and data sets.<br><br>About Malomatia<br><br> ABOUT US <br><br>malomatia is a leading Qatar-based IT services and solutions provider, bringing together top Qatari and international talent to deliver innovative, end-to-end technology solutions that empower clients to achieve their strategic goals.<br><br>Our mission<br><br>Empowering Qatar’s businesses and governments to leap into the digital future with agile, knowledge-driven solutions.<br><br>Our vision<br><br>To become Qatar’s trusted knowledge partner in digital transformation, disrupting industries, shaping the future, and building a world-class tech ecosystem.<br><br>Driving change that makes a real impact<br><br>Since 2008, malomatia has been driving Qatar’s digital transformation through innovative, ISO-certified IT solutions. With expertise across key public and private sectors, we empower the nation’s vision with advanced services in cloud, cybersecurity, AI, and contact center excellence, elevating the role of technology in shaping Qatar’s sustainable future.<br><br>About The Team<br><br>Established in 2008, malomatia is a Qatari leader in IT services and digital transformation. We serve key sectors including Government, Healthcare, Education, Customs, and Transportation, delivering impactful solutions that support national development goals. Powered by a diverse team of skilled Qatari and international IT professionals, we deliver innovative, high-value digital solutions tailored to the unique needs of our clients.<br><br>Our mission is to inspire customers to thrive through digital excellence, and we envision becoming the trusted partner of choice in building a smarter society through technology and talent. We are driven by core values that define our culture and approach: ownership, integrity, empathy, teamwork, transparency, agility, excellence, trust, and innovation.<br><br>Join us in shaping the future of technology in Qatar

CNTXT AI is a leading artificial intelligence company focused on building next-generation AI systems, products, and infrastructure. We specialize in developing multimodal AI, robotics, and intelligent agents, powered by high-quality real-world data. Data is at the core of our innovation. We invest heavily in data collection, annotation, and AI training pipelines to enable advanced systems such as embodied AI and Vision-Language-Action (VLA) models.<br><br>Role Summary<br><br>CNTXT AI is looking for a Robotics Data Collector to support the collection of high-quality robotics and egocentric data used to train AI models.<br>This role involves working hands-on with robotic systems, sensors, and real-world environments to capture multimodal datasets, including video, motion, and interaction data. You will play a key role in enabling the development of intelligent robotic systems and AI agents.<br>The ideal candidate is detail-oriented, technically curious, and comfortable working in lab and controlled real-world environments.<br><br>Key Responsibilities<br><br>1. Data Collection Execution Collect robotics and egocentric (first-person) data using:Cameras (handheld, head-mounted, or robot-mounted) Sensors (IMU, depth cameras, etc.) Execute data collection tasks based on predefined scenarios and protocols. Ensure consistent and accurate recording of actions, interactions, and environments.<br><br><br><br>2. Robotics Operation Support Assist in operating robotic systems (humanoid or mobile robots) during data collection. Support setup and calibration of:Cameras and sensors Recording systems Ensure proper functioning of hardware during experiments.<br><br><br><br>3. Data Quality & Validation Review collected data for:Completeness Clarity Accuracy Identify and flag issues such as:Missing data Recording errors Sensor misalignment Follow quality guidelines to ensure high usability for AI training.<br><br><br><br>4. Experiment Setup & Execution Prepare environments for data collection sessions. Execute tasks such as:Object manipulation Navigation scenarios Human-robot interaction recordings Follow detailed instructions to simulate real-world use cases.<br><br><br><br>5. Documentation & Reporting Maintain records of:Data collection sessions Equipment usage Issues encountered Provide feedback to improve data collection processes and protocols.<br><br><br><br>6. Safety & Compliance Follow all lab safety protocols and operational guidelines. Handle robotics equipment and sensors with care. Ensure compliance with data privacy and security requirements.<br><br><br><br>Required Qualifications<br>0–3+ years of experience Data collection, field operations, or lab environments Technical or hardware-related roles Comfortable working with:Cameras, sensors, and recording devices Basic computer systems and tools Strong attention to detail and ability to follow instructions precisely.<br><br><br><br>Preferred Skills Experience with robotics systems or hardware environments. Familiarity with:Egocentric or first-person data collection Computer vision or AI-related datasets Basic understanding of:Robotics concepts Sensors and data recording tools Experience working in technical labs or research environments.<br><br><br><br>Key Traits Detail-oriented and quality-focused Hands-on and execution-driven Reliable and consistent in following protocols Comfortable working in dynamic environments Curious about robotics and AI<br><br><br><br>Success Metrics Volume and quality of data collected Accuracy and completeness of datasets Adherence to data collection protocols Reduction in data errors and rework Efficiency in executing data collection tasks<br><br><br><br>Why Join CNTXT AIWork on cutting-edge robotics and AI systems Contribute to building next-generation intelligent agents Gain hands-on experience with robotics labs and real-world data Be part of a fast-growing, innovation-driven company

CNTXT AI is a leading artificial intelligence company focused on building next-generation AI systems, products, and infrastructure. We specialize in developing multimodal AI, robotics, and intelligent agents, powered by high-quality real-world data. Data is at the core of our innovation. We invest heavily in data collection, annotation, and AI training pipelines to enable advanced systems such as embodied AI and Vision-Language-Action (VLA) models.<br><br>Role Summary<br><br>CNTXT AI is looking for a Robotics Data Collector to support the collection of high-quality robotics and egocentric data used to train AI models.<br>This role involves working hands-on with robotic systems, sensors, and real-world environments to capture multimodal datasets, including video, motion, and interaction data. You will play a key role in enabling the development of intelligent robotic systems and AI agents.<br>The ideal candidate is detail-oriented, technically curious, and comfortable working in lab and controlled real-world environments.<br><br>Key Responsibilities<br><br>1. Data Collection Execution Collect robotics and egocentric (first-person) data using:Cameras (handheld, head-mounted, or robot-mounted) Sensors (IMU, depth cameras, etc.) Execute data collection tasks based on predefined scenarios and protocols. Ensure consistent and accurate recording of actions, interactions, and environments.<br><br><br><br>2. Robotics Operation Support Assist in operating robotic systems (humanoid or mobile robots) during data collection. Support setup and calibration of:Cameras and sensors Recording systems Ensure proper functioning of hardware during experiments.<br><br><br><br>3. Data Quality & Validation Review collected data for:Completeness Clarity Accuracy Identify and flag issues such as:Missing data Recording errors Sensor misalignment Follow quality guidelines to ensure high usability for AI training.<br><br><br><br>4. Experiment Setup & Execution Prepare environments for data collection sessions. Execute tasks such as:Object manipulation Navigation scenarios Human-robot interaction recordings Follow detailed instructions to simulate real-world use cases.<br><br><br><br>5. Documentation & Reporting Maintain records of:Data collection sessions Equipment usage Issues encountered Provide feedback to improve data collection processes and protocols.<br><br><br><br>6. Safety & Compliance Follow all lab safety protocols and operational guidelines. Handle robotics equipment and sensors with care. Ensure compliance with data privacy and security requirements.<br><br><br><br>Required Qualifications<br>0–3+ years of experience Data collection, field operations, or lab environments Technical or hardware-related roles Comfortable working with:Cameras, sensors, and recording devices Basic computer systems and tools Strong attention to detail and ability to follow instructions precisely.<br><br><br><br>Preferred Skills Experience with robotics systems or hardware environments. Familiarity with:Egocentric or first-person data collection Computer vision or AI-related datasets Basic understanding of:Robotics concepts Sensors and data recording tools Experience working in technical labs or research environments.<br><br><br><br>Key Traits Detail-oriented and quality-focused Hands-on and execution-driven Reliable and consistent in following protocols Comfortable working in dynamic environments Curious about robotics and AI<br><br><br><br>Success Metrics Volume and quality of data collected Accuracy and completeness of datasets Adherence to data collection protocols Reduction in data errors and rework Efficiency in executing data collection tasks<br><br><br><br>Why Join CNTXT AIWork on cutting-edge robotics and AI systems Contribute to building next-generation intelligent agents Gain hands-on experience with robotics labs and real-world data Be part of a fast-growing, innovation-driven company

CNTXT AI is a leading artificial intelligence company focused on building next-generation AI systems, products, and infrastructure. We specialize in developing multimodal AI, robotics, and intelligent agents, powered by high-quality real-world data. Data is at the core of our innovation. We invest heavily in data collection, annotation, and AI training pipelines to enable advanced systems such as embodied AI and Vision-Language-Action (VLA) models.<br><br>Role Summary<br><br>CNTXT AI is looking for a Robotics Data Collector to support the collection of high-quality robotics and egocentric data used to train AI models.<br>This role involves working hands-on with robotic systems, sensors, and real-world environments to capture multimodal datasets, including video, motion, and interaction data. You will play a key role in enabling the development of intelligent robotic systems and AI agents.<br>The ideal candidate is detail-oriented, technically curious, and comfortable working in lab and controlled real-world environments.<br><br>Key Responsibilities<br><br>1. Data Collection Execution Collect robotics and egocentric (first-person) data using:Cameras (handheld, head-mounted, or robot-mounted) Sensors (IMU, depth cameras, etc.) Execute data collection tasks based on predefined scenarios and protocols. Ensure consistent and accurate recording of actions, interactions, and environments.<br><br><br><br>2. Robotics Operation Support Assist in operating robotic systems (humanoid or mobile robots) during data collection. Support setup and calibration of:Cameras and sensors Recording systems Ensure proper functioning of hardware during experiments.<br><br><br><br>3. Data Quality & Validation Review collected data for:Completeness Clarity Accuracy Identify and flag issues such as:Missing data Recording errors Sensor misalignment Follow quality guidelines to ensure high usability for AI training.<br><br><br><br>4. Experiment Setup & Execution Prepare environments for data collection sessions. Execute tasks such as:Object manipulation Navigation scenarios Human-robot interaction recordings Follow detailed instructions to simulate real-world use cases.<br><br><br><br>5. Documentation & Reporting Maintain records of:Data collection sessions Equipment usage Issues encountered Provide feedback to improve data collection processes and protocols.<br><br><br><br>6. Safety & Compliance Follow all lab safety protocols and operational guidelines. Handle robotics equipment and sensors with care. Ensure compliance with data privacy and security requirements.<br><br><br><br>Required Qualifications<br>0–3+ years of experience Data collection, field operations, or lab environments Technical or hardware-related roles Comfortable working with:Cameras, sensors, and recording devices Basic computer systems and tools Strong attention to detail and ability to follow instructions precisely.<br><br><br><br>Preferred Skills Experience with robotics systems or hardware environments. Familiarity with:Egocentric or first-person data collection Computer vision or AI-related datasets Basic understanding of:Robotics concepts Sensors and data recording tools Experience working in technical labs or research environments.<br><br><br><br>Key Traits Detail-oriented and quality-focused Hands-on and execution-driven Reliable and consistent in following protocols Comfortable working in dynamic environments Curious about robotics and AI<br><br><br><br>Success Metrics Volume and quality of data collected Accuracy and completeness of datasets Adherence to data collection protocols Reduction in data errors and rework Efficiency in executing data collection tasks<br><br><br><br>Why Join CNTXT AIWork on cutting-edge robotics and AI systems Contribute to building next-generation intelligent agents Gain hands-on experience with robotics labs and real-world data Be part of a fast-growing, innovation-driven company

CNTXT AI is a leading artificial intelligence company focused on building next-generation AI systems, products, and infrastructure. We specialize in developing multimodal AI, robotics, and intelligent agents, powered by high-quality real-world data. Data is at the core of our innovation. We invest heavily in data collection, annotation, and AI training pipelines to enable advanced systems such as embodied AI and Vision-Language-Action (VLA) models.<br><br>Role Summary<br><br>CNTXT AI is looking for a Robotics Data Collector to support the collection of high-quality robotics and egocentric data used to train AI models.<br>This role involves working hands-on with robotic systems, sensors, and real-world environments to capture multimodal datasets, including video, motion, and interaction data. You will play a key role in enabling the development of intelligent robotic systems and AI agents.<br>The ideal candidate is detail-oriented, technically curious, and comfortable working in lab and controlled real-world environments.<br><br>Key Responsibilities<br><br>1. Data Collection Execution Collect robotics and egocentric (first-person) data using:Cameras (handheld, head-mounted, or robot-mounted) Sensors (IMU, depth cameras, etc.) Execute data collection tasks based on predefined scenarios and protocols. Ensure consistent and accurate recording of actions, interactions, and environments.<br><br><br><br>2. Robotics Operation Support Assist in operating robotic systems (humanoid or mobile robots) during data collection. Support setup and calibration of:Cameras and sensors Recording systems Ensure proper functioning of hardware during experiments.<br><br><br><br>3. Data Quality & Validation Review collected data for:Completeness Clarity Accuracy Identify and flag issues such as:Missing data Recording errors Sensor misalignment Follow quality guidelines to ensure high usability for AI training.<br><br><br><br>4. Experiment Setup & Execution Prepare environments for data collection sessions. Execute tasks such as:Object manipulation Navigation scenarios Human-robot interaction recordings Follow detailed instructions to simulate real-world use cases.<br><br><br><br>5. Documentation & Reporting Maintain records of:Data collection sessions Equipment usage Issues encountered Provide feedback to improve data collection processes and protocols.<br><br><br><br>6. Safety & Compliance Follow all lab safety protocols and operational guidelines. Handle robotics equipment and sensors with care. Ensure compliance with data privacy and security requirements.<br><br><br><br>Required Qualifications<br>0–3+ years of experience Data collection, field operations, or lab environments Technical or hardware-related roles Comfortable working with:Cameras, sensors, and recording devices Basic computer systems and tools Strong attention to detail and ability to follow instructions precisely.<br><br><br><br>Preferred Skills Experience with robotics systems or hardware environments. Familiarity with:Egocentric or first-person data collection Computer vision or AI-related datasets Basic understanding of:Robotics concepts Sensors and data recording tools Experience working in technical labs or research environments.<br><br><br><br>Key Traits Detail-oriented and quality-focused Hands-on and execution-driven Reliable and consistent in following protocols Comfortable working in dynamic environments Curious about robotics and AI<br><br><br><br>Success Metrics Volume and quality of data collected Accuracy and completeness of datasets Adherence to data collection protocols Reduction in data errors and rework Efficiency in executing data collection tasks<br><br><br><br>Why Join CNTXT AIWork on cutting-edge robotics and AI systems Contribute to building next-generation intelligent agents Gain hands-on experience with robotics labs and real-world data Be part of a fast-growing, innovation-driven company

Senior Consultant – Data Governance???? Location: UAE???? Full-Time | 3-Year Contract with 2-Year Extension Option???? 30,000 QRD /month We’re looking for a Senior Consultant in Data Governance to support the implementation and ongoing development of data governance practices across the organisation. This is a fantastic opportunity for a mid-level professional to contribute to key governance initiatives while building on their expertise in data quality, stewardship, and compliance frameworks. What You’ll DoSupport the rollout and operationalisation of data governance policies and standards Collaborate with business units to define data ownership and stewardship roles Assist with monitoring data quality metrics and reporting against KPIsHelp manage metadata and data cataloguing efforts Coordinate with IT and compliance teams to ensure governance aligns with internal policies and external regulations Promote data literacy and awareness across business teams What You Bring4–6 years of experience in data governance, data management, or related roles Exposure to governance tools (e.g., Collibra, Informatica, Microsoft Purview) Understanding of data privacy and compliance standards (GDPR, ISO 27001, etc.) Strong communication and stakeholder engagement skills A proactive and detail-oriented approach to solving data issues Relevant certifications (e.g., CDMP, ISO 27001 awareness) are a plus What We Offersalary of AED 40,000 (including Visa and relocation expenses)3-year renewable contract with a 2-year extension option The chance to work on high-impact data initiatives in a dynamic and supportive environment

Role Purpose<br><br>The Senior Manager, Data Architecture & Analytics leads client engagements covering data architecture, modelling, integration, engineering, platforms, statistics and analytics. The role helps organisations move from fragmented data environments to coherent target architectures that support trusted information, interoperability, secure reuse and decision-making. It connects business priorities and governance requirements with implementable technical designs and delivery roadmaps.<br><br>The Senior Manager directs architects, engineers, analysts and platform specialists; quality-assures technical deliverables; and facilitates decisions involving business, data, security and technology stakeholders. The role may recommend standards, patterns and solution options, but client architecture approvals and production authority remain with authorised client bodies. The position also ensures that technical work is documented, testable and transferable to client teams, with clear assumptions, dependencies, risks and transition requirements.<br><br>Key Responsibilities<br><br>Lead architecture, modelling, integration, engineering, platform and analytics workstreams across client engagements. Assess current data landscapes, information flows, platforms, interfaces, data stores, analytical capabilities and technical constraints. Develop architecture principles, current-state and target-state views, transition states and implementation roadmaps. Guide conceptual, logical and physical data modelling and ensure models are connected to business definitions and metadata. Define integration and interoperability patterns covering APIs, exchanges, pipelines, events and controlled data sharing. Evaluate platform and tool options against functional, non-functional, security, operational and cost requirements. Shape analytics, indicator, dashboard and data-product architectures that are traceable to business outcomes and trusted data. Ensure security, privacy, classification, quality, lineage, retention and resilience requirements are incorporated into designs. Facilitate architecture reviews and prepare options, trade-offs and recommendations for client approval. Direct technical teams, establish design quality gates and resolve cross-workstream dependencies or inconsistencies. Review technical specifications, models, interface designs, test evidence and transition plans before client submission. Develop client capability through walkthroughs, design rationale, documentation and structured handover.<br><br>Minimum Requirements<br><br>Education<br><br>Bachelor's degree in computer science, data engineering, information systems or a related field.master's degree preferred. An equivalent combination of relevant education and directly applicable consulting or implementation experience may be considered.<br><br>Professional Experience<br><br>Typically 10+ years in architecture, data engineering or analytics, including 4+ years in technical leadership. Demonstrated leadership of data-architecture, engineering, integration or analytics programmes in complex organisations. Experience translating business and governance requirements into technical designs and transition roadmaps. Experience managing architects, engineers, analysts, platform specialists and external technology providers. A record of presenting technical options and trade-offs to senior non-technical stakeholders.<br><br>Technical and Domain Knowledge<br><br>Enterprise and data-architecture methods, principles and governance. Conceptual, logical and physical data modelling. Integration patterns, APIs, data exchange, pipelines and interoperability. Cloud, on-premises and hybrid data-platform concepts. Analytics, reporting, indicator and dashboard architecture. Metadata, lineage, data quality and master-data design considerations. Security, privacy, access, retention, resilience and operational requirements. Technology evaluation, transition planning and technical debt management.<br><br>Core Competencies<br><br>Enterprise and data architecture. Data modeling. Analytics platforms. Integration patterns. Technical governance. Leadership. Systems thinking. Design governance. Technical judgement. Team leadership. Leading technical discovery and architecture workshops. Explaining complex designs and trade-offs to executive and business audiences. Producing clear architecture documents, roadmaps and decision records. Managing multidisciplinary technical teams and design dependencies. Challenging vendor proposals and validating technical evidence. Balancing strategic target state with realistic implementation constraints. Facilitating client approval without assuming formal architecture authority.<br><br>Preferred Certifications<br><br>TOGAF Enterprise Architecture Practitioner CDMP Practitioner or Master Cloud data certification<br><br>Focus areas<br><br>Enterprise and data architecture Data modeling Analytics platforms<br><br>Ready to apply for this role?<br><br>Apply for Senior Manager, Data Architecture & Analytics

Role Purpose<br><br>The Data Engineering Consultant designs, builds and supports reliable data pipelines, integrations and services for client data and analytics solutions. The role converts approved architecture, business requirements and governance controls into tested technical components that move, transform and deliver data with appropriate quality, metadata, lineage, security and operational monitoring.<br><br>The consultant works with architects, analysts, platform teams, security specialists and client system owners throughout design, development, testing and transition. The role may implement within client environments under authorised access, but production ownership and operational authority remain with the client. The expected outcome is maintainable engineering work with clear source-to-target logic, automated controls, deployment evidence, runbooks and knowledge transfer suitable for client operation after handover.<br><br>Key Responsibilities<br><br>Analyse approved requirements, source systems, target models, data volumes, schedules, controls and service expectations. Design and build batch, streaming or API-based data ingestion and transformation pipelines. Implement source-to-target mappings, business transformations, reference-data logic and data-standardisation rules. Embed validation, reconciliation, exception handling and data-quality controls within engineering workflows. Capture technical metadata, lineage, schedules, dependencies, ownership and operational information for delivered pipelines. Apply approved security, privacy, classification, access, encryption and logging requirements. Develop automated unit, integration, regression and data-validation tests and retain execution evidence. Optimise performance, scalability, reliability and cost within the approved architecture and platform constraints. Implement deployment automation, version control, configuration management and controlled release practices. Monitor pipeline operation, investigate failures and support defect resolution during implementation and transition. Prepare technical specifications, code documentation, support procedures, runbooks and handover records. Walk client engineers through design decisions, operating procedures and known limitations before transition.<br><br>Minimum Requirements<br><br>Education<br><br>Bachelor's degree in computer science, software engineering, data engineering or a related field. An equivalent combination of relevant education and directly applicable consulting or implementation experience may be considered.<br><br>Professional Experience<br><br>Typically 3-8 years in data engineering, integration, ETL/ELT, software or cloud data platforms. Experience in data engineering, integration, ETL/ELT, software development or cloud data delivery. Experience building and testing production-grade pipelines, APIs or data-processing services. Experience with version control, automated deployment, monitoring and operational support. Experience working from architecture, security and data-quality requirements in multidisciplinary teams.<br><br>Technical and Domain Knowledge<br><br>Data ingestion, transformation and orchestration patterns. SQL and one or more relevant programming or scripting languages. Batch, streaming, API and integration technologies. Cloud or enterprise data platforms and storage patterns. Data quality, reconciliation, exception handling and test automation. Metadata, lineage, source-to-target mapping and documentation. Security, access control, encryption, logging and secrets management. Version control, CI/CD, configuration and operational monitoring.<br><br>Core Competencies<br><br>SQL and programming. Data pipelines. APIs and integration. Cloud/data platforms. Testing and observability. Security and quality controls. Engineering discipline. Problem solving. Reliability focus. Automation mindset. Clarifying technical requirements and identifying missing decisions early. Estimating engineering effort, dependencies and delivery risk. Explaining technical designs and defects to mixed audiences. Producing maintainable documentation and auditable test evidence. Collaborating with client engineers, vendors and multidisciplinary teams. Working within controlled client access and change processes. Transferring engineering knowledge and supporting operational handover.<br><br>Preferred Certifications<br><br>Google Cloud Professional Data Engineer or comparable cloud data credential CDMP Associate or Practitioner<br><br>Focus areas<br><br>SQL and programming Data pipelines APIs and integration<br><br>Ready to apply for this role?<br><br>Apply for Data Engineering Consultant

Role Overview:<br><br>Design and manage scalable data infrastructure to support operational and analytical systems.<br><br>Key Responsibilities:<br><br>Build and maintain data pipelines and architectures Ensure data quality, performance, and availability Support real-time and batch data processing Collaborate with IT, security, and operations teams<br><br>Requirements:<br><br>Degree in Computer Science / IT or related8–10+ years in data engineering Strong experience with databases and big data technologies