Design, model, and implement graph data structures that capture complex system relationships, workflows, and time-dependent processes using Neo4j, Gremlin, or similar tools.Build and integrate web application back ends and contribute to front-end development as needed to deliver complete, production-ready features.Develop and maintain robust ETL and data pipelines spanning structured, semi-structured, and unstructured data, with strong attention to data quality.Engineer real-time and event-streaming workflows that handle high-velocity, sequential data flows.Deploy and operate enterprise applications in cloud environments using containerization and orchestration, applying DevOps, DataOps, and MLOps practices.Apply GenAI/ML techniques, including GraphRAG, to graph-related and NoSQL data problems.Write thorough unit, integration, and API tests to ensure robust, scalable, and maintainable solutions.Run simulations and apply advanced analytics in Python to solve complex mission problems.Align data engineering approaches with large-scale interconnected systems to ensure adaptability and scalability.
