Kamil Wang

I’m a Data Engineer focused on turning raw signals into business intelligence, with a hands-on bias toward reliability, performance, and cost control. I design resilient ETL and streaming pipelines and ship production data products that teams can build on confidently.

In my current role, I accelerated ETL throughput by 3.2x by redesigning ingestion pipelines with Python, Airflow, and bulk PostgreSQL loads—cutting job runtime from 90m to 28m. I also architected a cost-optimized AWS analytics stack (S3, Lambda, RDS, EKS), reducing monthly infra spend by 27%, while delivering GraphQL/REST backend services handling 1.2M requests/day with 99.95% uptime.

I improve observability and operational readiness by consolidating telemetry and logs into ELK and Prometheus, improving incident detection mean time to detect by 62%. I deploy containerized workloads with Docker and Kubernetes, automate releases with GitHub Actions, and strengthen data quality through schema validation, pytest, and SQL checks—reducing production data defects by 47%.

I’ve also partnered closely with product and ML teams to set KPIs and enable faster iteration cycles—integrating feature engineering pipelines to produce ML-ready datasets and orchestrating backups/disaster recovery for PostgreSQL and MongoDB with an RPO under 30 minutes. Earlier, I led front-end and UI initiatives across React/TypeScript and Next.js, coaching engineers and modernizing systems to improve performance and reduce regressions.