SHIVAM MEDAM

“Data engineer focused on building and operating reliable Airflow-orchestrated pipelines into BigQuery, including daily billing ingestion (~1GB/day) and ad platform (Facebook/LinkedIn) data collection. Implemented end-to-end data quality checks plus org-wide incident response automation integrating PagerDuty, Slack, and Jira, and has experience executing large backfills (4–5TB) via time-window batching.”

Pavanika Thotakura

Screened

Senior Data Engineer specializing in cloud big data pipelines and real-time streaming

Seattle, WA6y exp

“Amazon data engineer who built a real-time fraud detection pipeline for AWS Lambda, tackling multi-region telemetry quality issues and scaling stream processing for billions of daily requests. Strong in production-grade data/ML workflows on AWS (EMR, Glue, Kinesis, SageMaker) with hands-on entity resolution and anomaly detection.”

Andrew Fares

Screened

Mid-level Data Engineer specializing in AI, GenAI, and cloud data platforms

Seattle, WA4y exp

“Built production AI systems inside AWS finance/procurement, including an LLM-based supplier quote classification and price-vetting workflow that drove $5M in savings over 3 months. Combines GenAI evaluation expertise, internal platform design, and reusable Python data-quality tooling with strong cross-functional execution across finance, accounting, and hardware engineering.”

Shriya Bannikop

Screened

Mid-level Software Engineer specializing in cloud platforms, data engineering, and distributed systems

Seattle, WA5y exp

“Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.”