Role: GenAI Data Engineer (Senior)
Location/availability: US-based, full duration of the engagement. Client-facing role.
Context: Data engineering and generative AI engagement building data pipelines and graph-based data models, with a generative AI layer (RAG/GraphRAG) on top, delivered as part of a client-facing consulting team.
Key responsibilities:
Design, build, and maintain data pipelines and ETL workflows feeding a graph database model used by downstream applications; design and implement RAG/GraphRAG pipelines to power generative AI applications on top of the graph and data platform; work closely with data engineers and scientists to build and enhance data and AI-driven solutions; engage directly with client stakeholders gathering requirements, presenting progress, and supporting technical decision-making; collaborate within a small cross-functional delivery team.
Required skills: senior-level data engineering background (5+ years preferred) with strong Python proficiency; hands-on experience with Databricks (Snowflake a plus); experience with graph databases (e.g. Neo4j); hands-on experience with GenAI/LLM projects, including RAG and GraphRAG; experience with AWS or Azure cloud platforms; experience developing ETL pipelines and familiarity with ETL frameworks; direct client-facing experience, ideally from a consulting/professional-services background; experience with DevOps/CI-CD is a plus.