The ideal candidate will have extensive experience with a variety of database systems, both SQL and NoSQL, and will be responsible for the development, administration, and optimization of our database infrastructure. This role requires a deep understanding of database performance enhancement techniques, data replication, and high availability systems.

Key Responsibilities:

• Design, implement, and manage multi-database environments, including PostgreSQL, MSSQL, Cassandra, Click-house, Kafka KSQL, H2 database, and others.
• Manage high transactional OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) databases.
• Highly experienced in Query Optimization and DB Performance enhancements techniques
• Implement hands-on SQL, NoSQL, time-series and column-store DB solutions.
• Extensive experience in Database installation, configuration, version Upgrades and Migrations.
• Set up and manage streaming and logical database replication.
• Configure and maintain high availability and scalable clusters using tools like Patroni, Etcd, HAProxy, Pgpool, and Pgbackrest.
• Utilize PostgreSQL extensions such as PostGIS and TimescaleDB, etc
• Develop and maintain data archiving lifecycle processes.
• Implement data compression, partitioning and sharding strategies.
• Apply data engineering skills, including Python and shell scripting, to streamline and automate database operations.
• Establish and manage robust database backup policies.
• Ensure database security management and auditing.
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Skills

• Data/Information Architecture Experience: Demonstrated ability to design and implement scalable data architectures that support huge volumes of telematics and time-series data.
• Experience in FullText Search Within Database Features and Solr/Lucene Engines/Integrations: Proven track record in implementing full-text search capabilities within databases and integrating with Solr/Lucene engines to improve data retrieval efficiency.
• Data Visualizations and Dashboards, Building Using Grafana, PowerBI, Tableau, etc. Proficiency in creating intuitive and insightful data visualizations and dashboards that drive informed decision-making across the organization.
• Knowledge of geospatial analytics is highly desirable
• GenAI:
• 1 or 2 production deployments of GenAI DB integration.
• GenAI Architecture/Integration Skills: Expertise in designing and integrating GenAI solutions to meet diverse business needs.
• knowledge with Commercial/Open-Source LLM Models: In-depth knowledge of leveraging large language models, both commercial and open-source, to enhance data-driven applications.
• Machine Learning and Data Science Experience: Strong background in applying machine learning techniques and data science methodologies to solve complex problems and optimize processes.
• GenAI Low-Code Integration Platforms: Familiarity with low-code platforms for GenAI integration, enabling rapid development and deployment of AI solutions.
• Experience with advanced tools and frameworks like Langchain, LangGraph, and Llamaindex to facilitate innovative GenAI implementations.
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