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Abhinay Dodda
Mid-Level AI Engineer specializing in data pipelines and scalable ML systems
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About
Data engineer/backend developer with experience owning end-to-end, high-volume data pipelines for ML/analytics using Python, Airflow, SQL, and PySpark, reporting ~30% error reduction through improved reliability and data quality checks. Has also built Django-based REST APIs with caching/pagination and strong versioning practices, and operated external data collection/web scraping pipelines with anti-bot measures, monitoring, retries, and idempotent backfills.
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Key Strengths
- Owned end-to-end high-volume ML data pipelines (ingestion, validation, transformation, serving)
- Improved pipeline reliability and reduced errors by ~30%
- SQL performance tuning (join reduction, indexing/partitioning, aggregation optimization, query profiling)
- Scaled pipelines via Airflow parallelization and PySpark distributed processing
- Designed resilient external data collection with monitoring/alerts, retries, schema-change validation, and idempotent backfills
- Implemented anti-bot scraping strategies (rate limiting, user-agent/proxy rotation, headless browsers)
- Shipped customer/internal-facing REST APIs with caching, pagination, validation, monitoring, and clear documentation
- Managed API versioning and backward compatibility (v1/v2, additive changes, parallel versions for breaking changes)
- Stood up early-stage systems end-to-end with pragmatic tradeoffs, AWS deployment, CI/CD, and observability
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