وظائف مدخل بيانات في قطر

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>We are looking for a&nbsp;<strong>Lead Data Governance</strong>for one of our clients with the following details:</p><br> <p><strong>Start Date: September 2026&nbsp;</strong></p><br> <p><strong>Duration:&nbsp;31-Aug-2027</strong></p><br> <p><strong>Location:&nbsp;Doha,&nbsp;Qatar&nbsp;</strong></p><br> <p><strong>Work status: Residential, Single</strong></p><br> <p>QUALIFICATIONS &amp; EXPERIENCE&nbsp;</p><br> <ul> <li>Bachelor’s degree from an accredited university in Information Management or an engineering/business related equivalent.</li> <li>10+ years of experience in Data Management for Oil and Gas Upstream/Downstream Operations and Major Capital Projects.</li> <li>5+ years of experience in a management/lead position working through the definition and implementations of similar engineering information projects.</li> <li>Strong hands-on experience in building data governance strategy, framework, roadmaps, decision making bodies and on boarding data roles (data owners/stewards)</li> <li>Solid track record implementing scalable data governance technology stacks (including business glossary, data lineage, data quality)</li> <li>Good understanding of the data solutions used for different Data Management needs such as Data visualization and BI, data science, data warehouses/lakes, Master data Management, data modeling Enterprise Document Management solutions...etc</li> <li>Experience in Change Management, Program management and Stakeholder management</li> <li>Experience in data integration methods</li> <li>Good understanding of Upstream and Downstream DIM requirements</li> <li>Good Knowledge of Database systems, EDMS solutions and BI Technologies</li> <li>Good Knowledge of Applications Architecture, Information Security Principles</li> <li>Fluent English both spoke and written</li> </ul> <p>&nbsp;ACTIVITIES&nbsp;</p><br> <p><strong>Manage enterprise data governance framework, strategy, and maturity</strong></p><br> <ul> <li>Lead the data governance to promote data access, quality, and analytical capability. Governance can include a user training program, a data roles model, and data standards. Strives to reduce the cost of managing data and increase the value of the data.</li> <li>Lead the improvement of data literacy across&nbsp;COMPANY to upskill the organization on the value and use of data</li> <li>Measure enterprise data governance maturity and set yearly plans to improvement goals</li> <li>Represents the DM team and enterprise data stewards at leadership meetings. Develops and gives oral presentations on the power and value of data. Leads and/or serves on steering committees and helps leadership use its data effectively at these meetings. (i.e. Data Community, Data Council...etc)</li> <li>Applies expert knowledge and standards to analyze enterprise results and reports. Recommends and pursues collaboration and provides appropriate technical guidance to ensure the success of such collaborations. Interacts with business areas and IT on DM solutions.</li> </ul> <p><strong>Embed the data governance practices in AI, advanced analytics, digital use cases and data platform operations</strong></p><br> <ul> <li>Participate in scoping AI, Advanced Analytics, digital use cases and vendor proposals evaluations</li> <li>Ensure data quality rules are defined and developed, Data lineage for technical metadata are captured, business glossary is captured and approved by data stewards according to every digital use case data needs</li> <li>Establish and advance the enterprise AI Governance framework by defining AI agent operating boundaries, implementing governance controls and data quality assurance mechanisms, and delivering a strategic AI Governance roadmap that strengthens governance maturity, mitigates risk, and enables the responsible scaling of AI initiatives across the organization.</li> <li>Ensure the onboard of the digital use case owners and data stewards on the data governance tools to monitor their data usage, quality, and assignment</li> <li>Enable digital use cases master data management scope by defining the data quality checks</li> <li>Responsible for ensuring the data certification standard is followed, through the validation of data at source and destination are align for any data load or migration activity for digital use cases or application changes</li> </ul> <p><strong>Implement and maintain solutions to manage data governance</strong></p><br> <ul> <li>Lead the identification and configuration of data hierarchy, roles, catalog, quality, and business glossary for enterprise COMPANY data on Data Governance tools leveraging Oil and Gas standard practices</li> <li>Lead the prioritization, development and maintaining controls on data quality and sources to effectively manage risk associated with the use of data and analytics, as well as work with every entity to improve the finding and report issues to senior management per department</li> <li>Responsible for capturing business data challenges and propose solutions to overcome it</li> <li>Report the progress and challenges to senior management through Data Council and DPG Steer Co.</li> </ul> <p><strong>Defines polices, standards and guidelines for data governance</strong></p><br> <ul> <li>Lead the develop of data management policies, procedures, and guidelines relevant to the data management company needs</li> <li>Lead the development and implementation of enterprise metadata standards, guidelines, and processes to ensure quality metadata and support for ongoing data governance</li> <li>Ensure and monitor the adherence to all data policies, procedures, and guidelines</li> <li>Govern and overlooks the data sources to ensure its alignment with policies and best practices of handling stored data.</li> <li>Aligns with the data operations to ensure it fulfils the data governance requirements</li> <li>Upskills developees on data governance and management</li> </ul> <br> </div>

Hiring: Senior Data Architect (Data & AI) Location: Doha, Qatar Industry: Banking / Financial Services Experience: 12+ years overall (min. 7 years in Data Architecture) GCC/Qatar Banking Experience Mandatory<br>Role Overview Strategic role responsible for governing the Enterprise Data Architecture framework supporting Data Analytics and AI initiatives across the organization. Strong focus on Responsible AI, data governance, and enterprise-scale architecture design. Key Responsibilities Govern and oversee the Enterprise Data Architecture framework supporting Data Analytics and AI initiatives. Define and maintain conceptual, logical, and physical data models aligned with business, analytics, and AI requirements. Review and validate data architecture designs, end-to-end data flows, data lineage, and integration patterns for compliance with Data Governance, Data Quality, Security, and Privacy requirements. Assess AI use cases from a technical architecture lens — data sourcing, integration, scalability, performance, and alignment with target architecture. Establish technical controls for Responsible AI (RAI) — data validation, bias detection, explainability, traceability, and monitoring. Evaluate vendor solutions for alignment with enterprise architecture standards, integration, security, and performance. Conduct data-focused assessments of third-party solutions for data protection, privacy, and regulatory compliance. Review BRS, solution designs, and Post-Implementation Reviews (PIR) from a data architecture perspective. Govern data integration frameworks — ETL/ELT, APIs, streaming, and batch data flows. Support regulatory compliance initiatives, audits, and architecture governance forums. Act as SME in Data Governance, AI Governance, Responsible AI, and Architecture Review forums. Required Skills & Experience7–10+ years in Data Architecture, Enterprise Data Management, Data Engineering, or related disciplines — banking/financial services experience required, GCC/Qatar preferred. Strong grasp of enterprise data architecture, data modeling, integration, and governance frameworks. Hands-on knowledge of modern data platforms — data warehouses, lakehouses, ETL/ELT, analytics ecosystems. Understanding of AI/ML data ecosystems and Responsible AI principles. Experience reviewing architecture across on-prem, cloud, and hybrid environments. Familiarity with Data Governance, Data Quality, Metadata Management, and regulatory data requirements. Strong stakeholder management and communication skills across business, tech, risk, and compliance teams. Certifications such as TOGAF, DAMA, CDMP, or Cloud Architecture certifications preferred. Immediate joiners preferred.

Job Description<br><br>Hands-on senior Databricks specialist with proven experience in production enterprise environments. We are specifically looking for someone who can independently design, develop, troubleshoot, optimize, and govern Databricks solutions, rather than someone whose experience is limited to basic Databricks development.<br><br>Responsibilities<br><br>Design and implement enterprise-scale data solutions using Azure Databricks. Define and maintain Databricks data architecture and platform standards. Design data ingestion and integration pipelines from multiple source systems. Develop scalable ETL/ELT pipelines using Databricks and Apache Spark. Design and implement Medallion Architecture (Bronze, Silver, Gold) where appropriate. Work with Delta Lake and optimize Delta tables and data pipelines. Design data models and transformation processes for analytical and operational reporting. Integrate Databricks with Microsoft Dynamics 365 / Dataverse and other enterprise applications. Develop and optimize batch and near-real-time data processing pipelines. Implement data quality, validation, monitoring, lineage, and governance processes. Optimize Spark jobs, clusters, SQL queries, Delta tables, and data pipelines for performance and cost. Implement appropriate data security and access controls. Work with Unity Catalog for data governance, access control, cataloging, and lineage. Support Power BI and other analytical/reporting platforms through optimized data models and data services. Troubleshoot complex data engineering and performance issues. Establish development, testing, and production standards for Databricks. Support CI/CD and Dev Ops practices for Databricks solutions. Conduct technical reviews and mentor data engineers. Ensure data platform solutions meet security, availability, scalability, and disaster recovery requirements.<br><br>Qualifications<br><br>Minimum 8+ years of experience in data engineering/data architecture. Minimum 4+ years of strong hands-on experience with Azure Databricks. Strong hands-on experience with Apache Spark and PySpark. Strong experience with Delta Lake. Strong experience designing enterprise data platforms and data pipelines. Strong knowledge of Databricks Medallion Architecture. Strong experience with Unity Catalog, data governance, access control, and data lineage. Strong SQL skills and experience with large-scale data processing. Strong experience with Azure data services. Experience with Azure Data Factory / Azure Data Lake Storage Gen2. Experience integrating Databricks with APIs, enterprise applications, CRM systems, and other data sources. Experience with data modeling and dimensional modeling. Strong understanding of data quality and data governance. Strong understanding of performance optimization and Databricks cost optimization. Experience with CI/CD, Git, Azure Dev Ops, and deployment automation. Experience working with large-volume enterprise datasets. Ability to troubleshoot complex production data issues.<br><br>Preferred Certifications<br><br>Databricks Certified Data Engineer Professional Databricks Certified Data Engineer Associate Microsoft Certified: Azure Data Engineer Associate Other relevant Databricks/Azure certifications

We are looking for a Data Quality Lead to establish and manage the enterprise Data Quality Management Framework across the organization. The role will ensure data is accurate, complete, consistent, timely, and fit for purpose across banking, regulatory reporting, risk, finance, analytics, and AI initiatives. Key Responsibilities:Develop and implement Data Quality Framework, standards, policies, controls, KPIs/KRIs and scorecards. Define and monitor Data Quality Rules for Critical Data Elements (CDEs). Lead Data Quality Issue Management, including root-cause analysis, remediation, escalation, and closure. Monitor data quality through dashboards, scorecards and management reporting. Support regulatory reporting, risk, finance, compliance and audit requirements. Ensure data quality for AI, analytics and ML initiatives. Work closely with Data Owners, Data Stewards, IT, Risk, Finance, Compliance and Business teams. Drive enterprise-wide Data Governance and Data Quality maturity. Required Experience:8–12 years in Data Governance, Data Quality, Data Management, Risk Data or Regulatory Data. Banking/Financial Services or another highly regulated industry is required. Strong knowledge of Data Quality, Data Governance, Data Lineage, Metadata, MDM and Reference Data. Experience with Informatica, Collibra, Microsoft Purview, ABACUS or similar platforms. Strong stakeholder management and governance experience.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Key Responsibilities<br></span><ul><li>Design, build, and maintain scalable data infrastructure supporting AMI systems<br></li><li>Develop and manage data pipelines integrating multiple data sources into AMI platforms<br></li><li>Ensure data quality, consistency, availability, and performance for AMI monitoring and analytics teams<br></li><li>Design, optimize, and maintain databases capable of handling large-scale metering data volumes<br></li><li>Support real-time and batch data processing requirements<br></li><li>Collaborate with IT, cybersecurity, and operations teams to ensure secure and reliable data flow<br></li><li>Monitor system performance and resolve data pipeline issues and bottlenecks<br></li><li>Document data architecture, workflows, and operational procedures<br></li><li>Ensure compliance with IT governance, information security, and ISO standards<br></li><li>Support disaster recovery and business continuity planning related to data systems<br></li><li>Perform other duties as assigned by management<br></li></ul><br><span>RequirementsRequirements<br></span><ul><li>Bachelor's degree in Computer Science, Information Systems, or a related discipline<br></li><li>Cloud / Data Engineering certification (AWS, Azure, or GCP)<br></li><li>Minimum 9 years of relevant experience in data engineering or similar roles<br></li><li>Expertise in data pipeline design and development<br></li><li>Proficiency in databases and big data technologies (Hadoop, Spark)<br></li><li>Strong analytical, problem-solving, and system optimization skills<br></li><li>Experience working with large-scale data systems, preferably utility or AMI environments<br></li><li>Strong coordination and communication skills<br></li><li>Ability to work in cross-functional teams including IT, cybersecurity, and operations<br></li><li>Written and spoken English is essential; Arabic is preferred<br></li></ul><br> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><ul><li><p>Designs, builds, and maintains scalable data infrastructure supporting AMI systems.</p></li><li><p>Develops and manages data pipelines integrating multiple data sources into AMI platforms.</p></li><li><p>Ensures data quality, consistency, availability, and performance for AMI monitoring and analytics teams.</p></li><li><p>Designs, optimizes, and maintains databases capable of handling large-scale metering data volumes.</p></li><li><p>Supports real-time and batch data processing requirements.</p></li><li><p>Collaborates with IT, cybersecurity, and operations teams to ensure secure and reliable data flow.</p></li><li><p>Monitors system performance and resolves data pipeline issues and bottlenecks.</p></li><li><p>Documents data architecture, workflows, and operational procedures.</p></li><li><p>Ensures compliance with IT governance, information security, and ISO standards.</p></li><li><p>Supports disaster recovery and business continuity planning related to data systems.</p></li><li><p>Performs other duties assigned by management.</p></li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>Qualifications / Certifications: Bachelor’s degree in Computer Science, Information Systems, or a related discipline. Cloud / Data Engineering certification (AWS, Azure, or GCP)<br>Experience : Minimum 9 years of relevant experience in data engineering or similar roles.<br>Key Skills : </p><ul><li><p>Expertise in data pipeline design and development.</p></li><li><p>Proficiency with databases and big data technologies (Hadoop, Spark).</p></li><li><p>Strong analytical, problem-solving, and system optimization skills..</p></li><li><p>Written and Spoken English is essential; Arabic is preferred.<br><br>Working Conditions : Office-based technical role with coordination across IT and operations teams.</p></li></ul><p></p></section>

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.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <p>Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth.<br>The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner…</p><br><p><strong>What you will be doing?<br></strong>As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data.</p><br><p>Your responsibilities will include:</p><br><ul><li>Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms.</li><li>Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions.</li><li>Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions.</li><li>Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing.</li><li>Utilising Spark &amp;amp; Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics.</li></ul><p><strong>What we are looking for?</strong></p><br><ul><li>2-5 years: Data Engineer</li><li>Proficiency in Python, SQL, and database management.</li><li>Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark &amp;amp; Kafka.</li><li>Proven problem-solving skills and a solution-oriented mindset.</li><li>Experience working with business stakeholders either internally or externally</li><li>Excellent communication skills to collaborate effectively within teams and with stakeholders.</li><li>Strong business acumen with an interest in business-facing roles.</li><li>Adaptability and a start-up mentality to thrive in a dynamic environment.</li><li>Minimum of a bachelor's degree in Computer Science, Electronics, and Communication Engineering degrees.</li></ul><p>Artefact is the place to be: come and build the future of data and AI</p><br><p><strong>Innovation:</strong> We have a passion for creating impacting projects and believe innovation can come from anyone.<br><strong>Action:&amp;nbsp;</strong>We make things rather than telling people how to make them.<br><strong>Collaboration:&amp;nbsp;</strong>We believe in bringing talented people together, winning together, and in learning from each other.</p><br> </div>

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.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span><u><b>Job Summary</b></u> <br></span><p>The Senior Data Analyst is responsible to&nbsp;leverage data-driven insights to inform and guide strategic decision-making within an organization. This role involves analyzing large datasets, identifying trends, patterns, and opportunities, and translating complex data into actionable recommendations for the strategy team and senior management.</p><br> <br><br><u><b>Job Responsibilities 1</b></u> <br><p>Utilize advanced data analysis techniques to extract valuable insights from various data sources, supporting strategic initiatives and decision-making.</p><br> <p>Identify trends, patterns, and correlations within data to anticipate future market dynamics and strategic opportunities.</p><br> <p>Evaluate the performance of the organization's key metrics, products, or services to identify areas for improvement and growth.</p><br> <p>Analyze data related to competitors' activities, market positioning, and performance to inform competitive strategies.</p><br> <p>Conduct data-driven market research and segment analysis to identify target audiences, market trends, and potential growth areas.</p><br> <p>Provide data-backed insights and recommendations to support the development and refinement of strategic plans.</p><br> <p>Collaborate with the strategy team and senior management to provide data-driven insights that inform critical decisions.</p><br> <p>Perform scenario analysis to assess the potential outcomes of different strategic choices and their impact on business goals.</p><br> <p>Create clear and compelling data visualizations, charts, and dashboards to communicate complex insights effectively.</p><br> <br><br><u><b>Job Responsibilities 2</b></u> <br><p>Define and track key performance indicators (KPIs) aligned with strategic goals, and provide insights into their progress.</p><br> <p>Collaborate with cross-functional teams, including finance, marketing, and operations, to gather and analyze relevant data.</p><br> <p>Ensure data accuracy, consistency, and integrity throughout the analysis process.</p><br> <p>Prepare and present data-driven recommendations and insights to senior management and key stakeholders.</p><br> <p>Conduct hypothesis testing to validate assumptions and uncover insights that drive strategic initiatives.</p><br> <p>Serve as a subject matter expert on data analysis and insights, providing guidance to the strategy team and other departments.</p><br> <p>Proactively identify opportunities for innovation and improvement based on data insights.</p><br> <p>Identify potential risks and challenges through data analysis, helping the strategy team develop risk-mitigation strategies.</p><br><br><br><b>Additional Responsibilities 3</b> <br><br><u><b>Job Knowledge &amp; Skills</b></u> <br><p>Deep understanding of the popular data analysis tools and databases.</p><br> <p>High-level experience in methodologies and processes for managing large-scale bases.</p><br> <p>Demonstrated experience in handling large data sets and relational databases.</p><br> <p>Understanding of addressing and metadata standards.</p><br> <p>High-level written and verbal communication skills.</p><br> <p>ERP knowledge preferably SAP functional skills are a requirement to be successful in this role.</p><br><br><br><u><b>Job Experience</b></u> <br><p>Minimum 8 year(s) working experience, 5 year(s) relevant working experience, 2 year (s) GCC is a plus</p><br><br><br><u><b>Competencies</b></u> <br>Agility<br>AI Fluency<br>Business Intelligence Tools L3<br>Data Governance L3<br>Data Marts L3<br>Data Quality Assurance L3<br>KPI Understanding L3<br>Leadership<br>Quality<br>Resilience<br><br><br><u><b>Education</b></u> <br>Bachelor's Degree in Business Administration or any related field<br><br><br><br> </div>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><b>Infrastructure Data Engineer<br><br></b></p><p><b>Design and manage scalable data infrastructure to support operational and analytical systems.</b></p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p><strong>Requirements:</strong> Degree in Computer Science / IT or related 8 10+ years in data engineering Strong experience with databases and big data technologies</p><p></p></section>

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

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>We are looking for an experienced IT Data &amp; AI Specialist to design, develop, and maintain data engineering and AI solutions that support business operations and digital transformation initiatives.</p><p>Key Responsibilities</p><ul><li>Design, develop, and maintain scalable data pipelines and data platforms.</li><li>Collect, clean, and transform structured and unstructured data.</li><li>Build, train, test, and deploy Machine Learning and Generative AI models.</li><li>Develop dashboards, reports, and actionable business insights.</li><li>Integrate AI solutions with enterprise applications.</li><li>Ensure data quality, governance, security, and compliance.</li><li>Monitor and optimize data pipelines and AI model performance.</li><li>Collaborate with business and technical stakeholders to deliver data-driven solutions.</li><li>Document data models, pipelines, and AI implementations.</li></ul><p>Required Skills</p><ul><li>Data Analysis</li><li>Data Engineering</li><li>Generative AI</li><li>Python</li><li>SQL</li><li>Machine Learning</li><li>AWS / Azure / GCP</li><li>Data Pipelines</li><li>Data Warehousing</li><li>ETL</li><li>Data Visualization / BI Tools</li><li>Cloud Computing</li></ul><p>Preferred Skills</p><ul><li>Microsoft Copilot</li><li>Google Gemini Enterprise</li><li>Large Language Models (LLMs)</li><li>Prompt Engineering</li><li>AI Solution Integration</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"><b>Qualifications</b></p><ul><li>Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.</li><li>36 years of experience in Data Engineering, Data Analytics, AI, or Machine Learning.</li><li>Strong hands-on experience with Python and SQL.</li><li>Experience with Machine Learning frameworks.</li><li>Experience working with AWS, Azure, or GCP cloud platforms.</li><li>Strong analytical, communication, and problem-solving skills.</li></ul><b>Location Preference:</b><ul><li>Candidates willing to relocate to Qatar.</li></ul><p></p></section>

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.

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> About the job BUSINESS DATA ANALYST - SERVICENOW - INVESTMENT (BANKING) <p>Role Summary</p><br> <p>The Business Data Analyst analyses, documents, and governs conceptual data models and Information Objects across enterprise systems, maintaining the enterprise semantic standard within ServiceNow EA.</p><br> <p>Key Responsibilities</p><br> <ul> <li>Analyse conceptual data models across enterprise systems.</li> <li>Document and manage Information Objects within ServiceNow EA.</li> <li>Maintain the Information Object glossary and conceptual data model.</li> <li>Ensure consistent use of Information Objects across governance, architecture, and solution design.</li> <li>Collaborate with architects, business analysts, and data governance teams to align enterprise semantic standards.</li> </ul> <p>Required Experience &amp; Skills</p><br> <ul> <li>Minimum 3 years' experience in business analysis, enterprise architecture support, or data management.</li> </ul> <p>Preferred / Advantageous</p><br> <ul> <li>Hands-on ServiceNow EA experience (strongly preferred).</li> <li>Investment management or financial services exposure.</li></ul> <p>Vertical:</p><br> <p>Technology</p><br> <br> <br> </div>

<p>JOB SUMMARY RKH Qitarat is currently seeking a Senior Asset Data Analyst to join our team and drive service excellence across the Doha Metro and Lusail Tram networks. The role is responsible for maintaining the integrity of FRACAS databases and analysing asset and RAM (Reliability, Availability, Maintainability) performance to support effective asset management. The Senior Asset Data Analyst will validate RAM performance against defined targets, analyse asset failure trends using MMS, and develop dashboards and business intelligence reports for the Engineering &amp; Maintenance department. The role also includes administering MMS hardware and supporting servers, databases, and related IT systems to ensure high system availability, while guiding Asset Data Analysts on FRACAS and RAM processes.</p><p><strong>Desired Candidate Profile</strong></p><p>Candidates should have strong data analytics experience, knowledge of IBM Maximo Manage, FRACAS and RAM principles, and experience with relevant server, database, and IT systems.</p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span><span><span><span><span><span><span><u><b>Job Description:</b></u></span></span></span></span></span></span></span><b>Details of the Division and Team</b><p><span>Deutsche Bank Research is responsible for economic and financial analysis within Deutsche Bank Group and covers asset allocation and all major industry sectors. We analyse relevant trends for the bank in financial markets, the economy and society, highlight risks and opportunities and act as consultant for the bank, its clients and stake-holders. </span></p><br><p><span>You will join the dbDIG team (Data Insights Group) that transforms alternative data, advanced analytics and artificial intelligence into client-facing investment research products and publications. In this role, you will shape how research questions become scalable data products, production-ready models, interactive dashboards, and practical artificial intelligence solutions used by analysts and clients. You will work at the intersection of research, data engineering, visualization, and artificial intelligence and help to demonstrate the bank’s applied analytics capability externally</span></p><br><p><b>What we will offer you</b></p><br><p>A healthy, engaged and well-supported workforce is better equipped to do their best work and, more importantly, enjoy their lives inside and outside the workplace. That’s why we are committed to providing an environment with your development and wellbeing at its center.</p><br><p><u>You can expect: </u></p><br><ul><li><p>Life Insurance&nbsp;</p><br></li><li><p>Accidental Death Insurance</p><br></li><li><p>&nbsp;Medical Insurance for you, your spouse and dependent children in country.</p><br></li><li><p>Flexible working arrangements</p><br></li><li><p>30 days of annual paid leave, plus public holiday &amp; Flexible Working Arrangement</p><br></li></ul><p><b>Your key responsibilities</b></p><br><ul><li><p><span>Drive the end-to-end alternative data agenda, partnering with analyst teams to turn research questions into scalable data products, from problem framing and data acquisition through signal development, statistical modeling, validation, and quality assurance.</span></p><br></li><li><p><span>Own data ingestion and validation standards for alternative datasets, using statistical, machine learning, and artificial intelligence-based checks to identify anomalies early and maintain high-quality inputs for modeling.</span></p><br></li><li><p><span>Collaborate with internal stakeholders across the full project lifecycle, while mentoring and helping manage junior team members working on data science projects.</span></p><br></li><li><p><span>Enhance data reporting by creating interactive dashboards, applications, geospatial maps, animations, and advanced visualizations.</span></p><br></li><li><p><span>Build practical artificial intelligence integrations, including application programming interfaces, model connection points, and secure access to internal data and research environments, to automate repetitive work and improve analyst productivity.</span></p><br></li></ul><p><b>Your skills and experience</b></p><br><ul><li><p><span>Experience building or managing alternative data, advanced analytics, or machine learning products in a research, financial services, or data-driven environment.</span></p><br></li><li><p><span>Strong capabilities in Python, PySpark, Tableau, data extraction, data quality testing, and working with large datasets in database or distributed computing environments.</span></p><br></li><li><p><span>Ability to translate complex research questions into clear analytical approaches, validated signals, and production-ready data products.</span></p><br></li><li><p><span>Experience creating dashboards, visualizations, or applications that make complex data easy for analysts and clients to understand and use.</span></p><br></li><li><p><span>Strong stakeholder management skills, with the ability to partner across research, technology, data engineering, and client-facing teams.</span></p><br></li><li><p><span>Proven ability to leverage AI tools to enhance productivity, optimize workflows to solve business problems, while applying critical judgment to ensure responsible and compliant use of data and AI outputs.</span></p><br></li></ul><p><b>How we’ll support you</b></p><br><ul><li><p>Flexible working to assist you balance your personal priorities</p><br></li><li><p>Coaching and support from experts in your team</p><br></li><li><p>A culture of continuous learning to aid progression</p><br></li><li><p>A range of flexible benefits that you can tailor to suit your needs</p><br></li><li><p>Training and development to help you excel in your career</p><br></li></ul><p><b>About us and our teams</b></p><br><p>Deutsche Bank is the leading German bank with strong European roots and a global network. Click here to see what we do.</p><br><p><b>Deutsche Bank &amp; Diversity</b></p><br><p>We strive for a <span><u>culture</u></span> in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively.</p><br><p>Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group.</p><br><p>We welcome applications from all people and promote a positive, fair and inclusive work environment.</p><br> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> Job Summary <br> <p>The Associate, Data Science plays a foundational role in supporting data science initiatives across the bank. The role involves working under the guidance of senior team members to build and deploy machine learning models, conduct exploratory data analysis, and generate data-driven insights to solve business problems. The associate collaborates with business units to understand requirements, supports model development, and contributes to building scalable data science assets that align with QNB’s strategic goals.</p><br> <br> <br><br> Main Responsibilities <br> <p>A. Shareholder &amp; Financial: - Support the development and tracking of KPIs to measure impact of data science initiatives. - Assist in delivering data analytics solutions that drive business efficiency and revenue growth. - Take part in the overall QNB Data &amp; Analytics strategy execution. - Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. - Act within the limits of the powers delegated to the incumbent. </p><br><p>B. Customer (Internal &amp; External): - Work with internal stakeholders to understand business needs and translate them into data problems. - Assist in preparing clear, concise, and insightful reports or dashboards for business users. - Support model testing and deployment activities, ensuring stakeholder alignment and timely delivery. - Ensure activities are conducted in accordance with Service Level Agreements (SLAs) with internal departments and units to achieve significant improvements in turnaround times. - Provide precise and timely data to external and internal auditors, compliance teams, financial control, and risk management when required. - Build and maintain strong/effective relationships with related departments/units to achieve the Group’s objectives. - Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. </p><br><p>C. Internal (Processes, Products, Regulatory): - Support the AVP and other senior data scientists in developing machine learning and statistical models. - Prepare and clean large datasets for analysis and modelling purposes. - Contribute to the implementation of AI/ML pipelines and production-ready solutions. - Document methodologies, outcomes, and learnings for reproducibility and scaling. - Develop predictive models using a variety of advanced machine learning techniques to extract meaningful insights. - Research and implement cutting-edge techniques and tools in data analytics and artificial intelligence to streamline data analysis processes and enhance decision-making. - Identify and implement new statistical or mathematical methodologies as required for specific data-driven projects. - Build robust data-driven models to address complex business questions and employ large-scale experimentation, analysis, and visualization techniques to generate efficient and repeatable insights. </p><br><p>D. Learning &amp; Knowledge: - Stay updated on the latest trends in machine learning, AI, and analytics tools. - Participate in training programs and learning sessions to build advanced analytics capability. - Proactively seek feedback and mentorship from senior team members. - Seek out opportunities to stay current with advancements in data analytics fields. - Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects.</p><br> <br> <br><br> Education and Experience Requirements <br> <p>- Bachler Degree University in data science, Computer Science, Mathematics, Engineering, or a related field. </p><br><p>- Familiarity with machine learning techniques, data wrangling, and model evaluation practices. </p><br><p>- High Level knowledge in data science tools like Python, R and Jupiter notebooks is desirable.</p><br> <br> <br> </div>

<p>Guildhall is currently supporting a leading engineering company in Doha, Qatar on major road infrastructure and pavement asset management projects. We are currently recruiting for an experienced Pavement Data Collection / Processing Engineer to join their growing team. This is a key role responsible for processing, validating, and quality checking pavement condition data while ensuring the highest standards of accuracy, compliance, and technical excellence across pavement survey projects. Key Responsibilities: - Process, validate, and analyze pavement condition data collected from automated survey systems, ensuring accuracy, consistency, and compliance with project specifications. - Perform QA/QC reviews of pavement data, identify discrepancies, implement corrective actions, and maintain high-quality documentation throughout project delivery. - Conduct pavement condition assessments, evaluate pavement distresses, and support pavement asset management in accordance with ASTM D6433, LTPP, and PCI standards. - Utilize LCMS-2, ROMDAS, Data View, PMS, and GIS platforms (ArcGIS/QGIS) to process, manage, and visualize pavement survey data. - Collaborate with project teams to prepare technical reports, provide project updates, and support the successful delivery of pavement engineering projects.</p><p>-Bachelor's Degree in Civil Engineering, Pavement Engineering, Transportation Engineering, or a related discipline -5–10 years of experience in pavement engineering, pavement condition assessment, or pavement asset management -Strong experience in QA/QC of processed pavement condition data and pavement distress rating -Hands-on experience with LCMS-2 is essential -Experience reviewing and validating pavement distress data, including cracking, rutting, ravelling, bleeding, texture, and roughness -Good understanding of ASTM D6433, LTPP, and pavement condition rating systems (PCI preferred) -Familiarity with ROMDAS, Data View, or similar pavement data processing software -Experience with Pavement Management Systems (PMS) is highly desirable -GCC or international pavement survey project experience is preferred -Experience with ARAN, Hawkeye, or other pavement data collection systems is an advantage -Knowledge of ArcGIS or QGIS is beneficial -Basic Python or R scripting skills for data validation or automation are a plus</p>

<p>Guildhall is currently supporting a leading engineering company in Doha, Qatar on major road infrastructure and pavement asset management projects. We are currently recruiting for an experienced Pavement Data Collection / Processing Engineer to join their growing team. This is a key role responsible for processing, validating, and quality checking pavement condition data while ensuring the highest standards of accuracy, compliance, and technical excellence across pavement survey projects. Key Responsibilities: - Process, validate, and analyze pavement condition data collected from automated survey systems, ensuring accuracy, consistency, and compliance with project specifications. - Perform QA/QC reviews of pavement data, identify discrepancies, implement corrective actions, and maintain high-quality documentation throughout project delivery. - Conduct pavement condition assessments, evaluate pavement distresses, and support pavement asset management in accordance with ASTM D6433, LTPP, and PCI standards. - Utilize LCMS-2, ROMDAS, Data View, PMS, and GIS platforms (ArcGIS/QGIS) to process, manage, and visualize pavement survey data. - Collaborate with project teams to prepare technical reports, provide project updates, and support the successful delivery of pavement engineering projects.</p><p>-Bachelor's Degree in Civil Engineering, Pavement Engineering, Transportation Engineering, or a related discipline -5–10 years of experience in pavement engineering, pavement condition assessment, or pavement asset management -Strong experience in QA/QC of processed pavement condition data and pavement distress rating -Hands-on experience with LCMS-2 is essential -Experience reviewing and validating pavement distress data, including cracking, rutting, ravelling, bleeding, texture, and roughness -Good understanding of ASTM D6433, LTPP, and pavement condition rating systems (PCI preferred) -Familiarity with ROMDAS, Data View, or similar pavement data processing software -Experience with Pavement Management Systems (PMS) is highly desirable -GCC or international pavement survey project experience is preferred -Experience with ARAN, Hawkeye, or other pavement data collection systems is an advantage -Knowledge of ArcGIS or QGIS is beneficial -Basic Python or R scripting skills for data validation or automation are a plus</p>