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Bhavya Sree Ganja
Senior Data Engineer specializing in cloud lakehouse platforms and streaming analytics
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About
Data engineer focused on fraud and banking analytics who has owned end-to-end batch + streaming pipelines at very large scale (hundreds of millions of records/day). Built robust data quality/observability layers (schema validation, anomaly detection, alerting) and delivered low-latency serving via AWS Lambda/API Gateway with DynamoDB + Redis, plus external data ingestion/scraping pipelines orchestrated in Airflow with anti-bot protections.
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Key Strengths
- Owned high-volume banking transaction pipelines end-to-end (hundreds of millions of records/day)
- Built Python-based data validation framework (schema validation, null checks, anomaly detection)
- Handled streaming late-arriving and duplicate events using deduplication + Spark watermarking
- Designed resilient external data ingestion with Airflow orchestration and raw-to-curated quality gates
- Implemented anti-bot strategies for scraping (rotating headers, throttling, rate limits)
- Shipped low-latency data APIs using Lambda/API Gateway with DynamoDB + Redis caching
- API versioning strategy to maintain backward compatibility (v1/v2, extend vs break fields)
- Stood up an ambiguous early-stage real-time fraud pipeline with pragmatic tech choices and iteration
- Set up CI/CD and infrastructure automation (GitHub Actions, Terraform) plus observability/runbooks
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“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”
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