Senior Data Engineer II

Sr Data Engineer II oversees all technical aspects of data architecture and database management, ensuring optimal performance and security, while leading teams and collaborating with architects and product teams to design and implement effective data solutions, including advanced Big Data management strategies through partitioning and indexing.

Education Qualifications:

- Bachelor’s degree in Computer Science, Computer Engineering, and/or comparable experience; advanced degree preferred
- Knowledge of Big Data / NoSQL design and development with variety of data stores (document, column family, graph, etc.)
- Knowledge of database management system products and ecosystem – e.g., storage formats, access algorithms, data management processes, administration, data maintenance, replication, high availability, encryption, etc.”
- Knowledge of distributed (multi-tiered) systems, algorithms, and relational & non-relational databases
- Knowledge of XML/JSON and schema development/reuse, relational database management systems, Open Source

Work Experience:

- Data engineering and development experience or a related job
- Experience in SQL and Python (or any other programming language like Java)
- Experience in design and development across one or more database management systems (e.g., HBase, Hive, GCP tools, NoSQL, BigTable, BigQuery, Spanner, IMS, DB2 zOS, Oracle, MS SQL Server, PostgreSQL, Netezza (PDA/DB2AA) as appropriate
- Experience in NoSQL databases (e.g., MongoDB, Couchbase, Cassandra, and Redis)
- Experience in data modeling tools (e.g., ErStudio, ErWin)
- Experience in performance tuning in the Big Data space
- Experience in distributed (multi-tiered) systems, algorithms, and application development
- Experience in database development and support of online transaction processing and/or online analytical processing systems
- Experience in software delivery methodology (Agile, Scrum, Agile XP, Test-Driven Development, Waterfall, etc.)
- Experience in infrastructure design for performance (e.g., network-attached or local-attached storage integration - such as Nutanix)
- Experience designing and implementing ETL/ELT pipelines and large-scale data-processing solutions.
- Experience with performance tuning, resiliency, high availability, data replication, and production troubleshooting.
- Experience with software-engineering practices including Git, automated testing, CI/CD, code reviews, and production support .
- Ability to collaborate effectively with architects, engineers, product teams, and business stakeholders.
- Experience mentoring engineers and providing technical leadership on complex initiatives.
AI / GenAI Experience – Preferred
- Working knowledge of Generative AI and LLM-based application architectures .
- Exposure to RAG, embeddings, vector databases, semantic/hybrid search, and knowledge retrieval .
- Experience integrating LLM APIs or frameworks such as LangChain/LangGraph is advantageous.
- Basic Understanding of AI evaluation, grounding, guardrails, observability, security, and responsible AI concepts.
- Experience building data pipelines for unstructured/semi-structured content and preparing enterprise data for AI consumption.
- Ability to rapidly prototype AI/GenAI use cases using Python and transition viable POCs toward production.