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Shashank R
Senior Data Engineer specializing in cloud data platforms and real-time analytics
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About
Data engineer (Credit One) who built and owned real-time financial transaction and credit risk/fraud data systems end-to-end on AWS + Snowflake. Delivered high-scale pipelines (150k events/hour; ~2TB/week), raised data accuracy to 99%, and cut Snowflake costs 42% while adding strong observability, schema-drift handling, and production-grade APIs/documentation.
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Key Strengths
- Owned end-to-end financial transaction data pipeline (real-time + batch) at scale (150k events/hour; ~2TB/week)
- Improved data accuracy to 99% via layered validation (PySpark + SQL/Snowflake checks)
- Built robust reliability controls: CloudWatch alarms, automated retries, DLQs to prevent data loss
- Handled upstream schema drift with dynamic schema detection and staging-layer isolation
- Reduced Snowflake compute costs by 42% using clustering, materialized views, and auto-suspend policies
- Designed resilient large-scale web scraping system (millions of records/week) with anti-bot mitigation and schema-change detection
- Shipped Flask-based data APIs with caching/indexing, automated tests, semantic versioning, and Swagger docs
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