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Sathyavarthan Balachandar
Mid-level Data Engineer specializing in scalable pipelines, Spark, and cloud data warehousing
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Backend/data platform engineer who recently owned an end-to-end large-scale financial data platform delivering real-time decision support for finance and operations. Has hands-on experience modernizing legacy batch pipelines into AWS cloud-native ELT with parallel-run cutovers, strong data quality controls (dbt-style tests, reconciliation), and measurable improvements in runtime, cost, and SLA compliance. Also builds scalable, secure FastAPI microservices using Docker, ALB-based horizontal scaling, Redis caching, and managed auth with Cognito/Supabase plus Postgres RLS.
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Key Strengths
- End-to-end ownership of large-scale data platform supporting finance/operations real-time decisioning
- Improved processing time ~30% by migrating from pandas-based ETL to Spark
- Improved SLA compliance ~25% via Airflow orchestration and retry logic
- Reduced data quality errors ~30% through reconciliation checks and stricter validation
- Led legacy batch pipeline modernization to cloud-native ELT on AWS with parallel run and incremental rollout
- Cut pipeline runtime >50% and reduced costs ~30% during migration while maintaining reporting consistency
- Strong API engineering practices in FastAPI (microservices, Pydantic validation, async I/O, Docker, ALB scaling, Redis caching)
- Production security implementation using managed auth (Cognito/Supabase), JWT, RBAC, and database-enforced RLS
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Mid-level Data Engineer specializing in cloud-native ETL, Spark, and real-time analytics
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