Data & GenAI Engineer

The Data & GenAI Engineer will design and own data pipelines and GenAI-driven services, transforming enterprise data into high-quality datasets and production-ready product capabilities. This role requires strong data engineering depth, backend API development, and occasional frontend integration to ship scalable systems end-to-end.

Responsibilities

• Data Engineering: Design and own batch/streaming ETL/ELT pipelines using Medallion architecture (Bronze, Silver, Gold). Build scalable transformations with Spark/Databricks, implement data validation, monitoring, lineage, and observability.
• GenAI Engineering: Design and improve production RAG systems, including ingestion, chunking, embedding pipelines, indexing, and retrieval optimization. Work with vector search systems, optimize prompt templates, and define evaluation metrics for retrieval quality, hallucination reduction, and latency.
• Backend & Full-Stack: Design and implement backend APIs using FastAPI, build microservices, and integrate with frontend applications. Collaborate with frontend teams to ensure data contracts and performance alignment.

Requirements

• 3-5 years of relevant industry experience in Data Engineering or Backend Engineering.
• Strong Python and advanced SQL skills.
• Hands-on experience with Spark/Databricks and performance optimization.
• Deep understanding of Medallion architecture and production data systems.
• Practical understanding of LLMs, RAG, embeddings, and vector search.
• Experience building and deploying REST APIs and understanding of system design basics.

Preferred Qualifications

• Frontend exposure (React/Angular).
• Experience with API gateways, microservices, CI/CD pipelines, and containerization (Docker).
• Experience with GenAI evaluation frameworks and cloud cost optimization.