I'm a data engineer with 4+ years building the pipelines, data models, and backend services that turn messy, high-volume data into something teams can actually trust and use. I currently build large-scale data migration pipelines and internal data SDKs for a US product company (remote). What I can help you with • Data pipelines & ETL/ELT — design, build, and optimize batch and streaming pipelines in Python and SQL, with workflow orchestration (Temporal/Airflow-style) • SQL & PostgreSQL performance — query optimization, indexing, partitioning, and materialized views (I've cut query times by ~85%) • Data migration & warehousing — schema/path design and zero-downtime migrations (moved ~9TB / 3M+ records with zero downtime) • Reporting & analytics infrastructure — dashboards, KPI tracking, and automated reporting (Metabase) • Backend APIs & services — FastAPI, Node.js/Express, REST, and microservices on AWS/Azure with Docker & Kubernetes A few results I'm proud of • Scaled a data pipeline from 500K to 6M+ daily events at 99% uptime • Recovered $20K/month in revenue by fixing a data attribution gap • Built an internal Python SDK with 100% test coverage, adopted org-wide I care about clean, well-tested, well-documented work and clear communication. I also write publicly about data and SQL — 17+ technical articles on PostgreSQL, Python, and system design. Whether you need a reliable data pipeline, a database that stops crawling under load, or a solid backend behind your product, send me your project details and I'll tell you exactly how I'd approach it.