Build and scale end-to-end ETL/ELT pipelines (batch and near-real-time), design ingestion systems, optimize cloud data warehouses, enforce data quality and monitoring, define data models/contracts, enable ML/AI workflows, and operate data infrastructure using Python, PostgreSQL, MongoDB, and AWS.

Design, build, and deploy agentic AI systems and LLM integrations for production. Implement RAG, vector stores, orchestration, monitoring, safety, evaluation, and tooling. Collaborate with product, data, and backend teams on AWS-hosted microservices, data pipelines, and integrations with PostgreSQL and MongoDB.