ujwal nivas

I’m a Data Engineer with 4.5+ years of experience building and maintaining large-scale data platforms and enterprise data warehouses. I’m known for ownership, problem-solving, and a process-driven approach to shipping dependable pipelines.

In my current role, I own and maintain healthcare data pipelines that process very large JSON (100–200 GB) and CSV datasets. I design and refactor Airflow DAGs in Python, build optimized BigQuery transformations with complex SQL (including partitioning and clustering), and lead tech-debt cleanup to keep critical workflows stable and fast.

I focus on performance optimization and measurable cost reduction—cutting end-to-end release timelines from ~1.5 months to ~2 weeks and achieving ~30% cost reduction by optimizing storage usage, processing logic, and avoiding unnecessary data movement. I also strengthen reliability through smarter processing to prevent reprocessing unchanged data, plus logging, monitoring, and alerting; earlier, I contributed to enterprise EDW solutions on AWS, mentored junior engineers, and earned 10/10 CSAT ratings for consecutive years.