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kireeti Sangarsh
Mid-level Data Engineer specializing in cloud ELT pipelines and analytics engineering
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Data engineer who has owned end-to-end ELT pipelines on Airflow + AWS (S3/Glue/Lambda) with Snowflake/Redshift, processing millions of records per day and tens of GBs via PySpark. Built strong data quality and reliability practices (40% quality improvement, 99%+ uptime), and also designed a resilient web-scraping system with anti-bot defenses and schema-change versioning plus REST APIs for serving curated data.
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Key Strengths
- Owned end-to-end ELT pipelines (ingestion → validation → transformations → serving) on AWS + Airflow with Snowflake/Redshift
- Scaled data processing to a few million records/day and PySpark jobs processing tens of GBs
- Implemented schema/null/duplicate/business-rule checks with monitoring; improved data quality by 40%
- Achieved 99%+ pipeline uptime through reliability practices and monitoring
- Designed resilient web scraping pipeline with retries (exponential backoff), checkpointing, and backfill support
- Handled anti-bot measures (rotating user agents, throttling, proxy/IP rotation) and schema-change resilience (versioned parsers, fallback logic, data contracts)
- Shipped versioned REST APIs with performance optimizations (caching, indexing, efficient SQL) plus documentation and tests
- Led early-stage data platform delivery via MVP scoping, CI/monitoring setup, and post-launch incident management (alerts, RCA, rollback/fix cycles)
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