lalit Patel

I'm a Data Engineer with 3+ years of experience designing and shipping production-grade ETL/ELT pipelines and cloud-native lakehouses on GCP and AWS. At Nucleusteq, I've architected and maintained 15+ batch and real-time pipelines using PySpark on Databricks — improving pipeline reliability by 35% across 1,800+ ETL jobs, cutting BigQuery query latency by 40%, and automating workflows that save the team 25+ engineering hours a week.

I focus on real-time streaming (Google Pub/Sub, Kafka) and Delta Lake Medallion architectures (Bronze/Silver/Gold) that keep data trustworthy, well-governed, and fast to query. I've also built metadata-driven ingestion frameworks that cut new data source onboarding time by 60%, and a data quality framework running 500+ automated checks a day across 20+ datasets — cutting manual validation effort by 80%.

Certified in Databricks Lakehouse Fundamentals, with AWS Cloud Developer Associate in progress. B.Tech in Computer Science from IET-DAVV, Indore.

Outside core pipeline work, I compete in C++ problem-solving and build small AI-powered tools on the side — including a multi-agent research/writing pipeline and a risk-detection agent, both on the Claude API.

I'm looking for remote Data Engineering, Cloud/ML Engineering, or BI-adjacent roles where I can keep building data infrastructure teams actually trust.