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Bhanu Prakash Reddy Dakilli
Mid-level Data Engineer specializing in Azure ETL/ELT and data warehousing
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Data engineer who has owned end-to-end production pipelines for customer transaction data (~2–5 GB/day) using Python/PySpark/SQL and Airflow, delivering major reliability and speed gains (70% faster reporting; 60–70% fewer data issues). Also built a daily external web-scraping system with anti-bot handling and safe, idempotent Airflow-driven backfills, plus a Python data API optimized with indexing/caching and tested for correctness.
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Key Strengths
- Owned end-to-end transaction data pipeline (API/CSV to warehouse) processing ~2–5 GB/day
- Implemented robust data quality framework (null/duplicate/schema/consistency/threshold checks) with automated Airflow alerts
- Reduced reporting time by ~70%
- Reduced data issues/error rates by ~60–70% through validation and monitoring
- Designed web scraping pipeline with anti-bot mitigations (rate limiting, user-agent rotation) and retry-with-delay
- Built parameterized Airflow backfills with idempotency and partition-based loading to prevent duplicates
- Improved API performance via SQL optimization, indexing, and caching; ensured correctness with validation and unit tests
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