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somasekhar G
Mid-level Data Engineer specializing in cloud big data and streaming pipelines
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Data engineer focused on large-scale financial data platforms, with hands-on ownership of an AWS + Databricks + Snowflake pipeline processing ~2TB/day. Strong in data quality (Great Expectations), schema drift automation, and production reliability (99.9%), plus measurable performance/cost wins (4h→1.2h, ~25% cost reduction). Also built an async Python crawling/ingestion framework with anti-bot mitigation, retries, and Airflow-driven backfills.
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Key Strengths
- Owned end-to-end AWS/Databricks/Snowflake pipeline ingesting ~2TB/day for a large financial client
- Improved pipeline reliability to 99.9% via Great Expectations validation and automated checks
- Reduced processing time from ~4 hours to ~1.2 hours through Spark optimization
- Cut cluster costs ~25% using join optimization, caching, and partitioning
- Built dynamic schema inference to handle schema drift without breaking downstream jobs
- Implemented robust external data collection with async crawling, retries/queues, and anti-bot defenses
- Operationalized deployments and monitoring with Azure DevOps CI/CD, Datadog alerting, and Azure Monitor
- Designed safe backfill strategy using Airflow concurrency controls and checkpointing
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3 publications
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