Vetted Amazon Redshift Professionals

“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.”

Sona Petrosyan

Screened

Director-level Engineering Leader specializing in Identity & Access Management

San Ramon, CA20y exp

“Senior engineering leader with 20+ years of experience spanning hands-on engineering and 7+ years of management across startups and enterprise, including Salesforce/MuleSoft, Airbnb, and Insightly. Particularly strong in platform security and IAM, with a track record of leading high-scale foundational services, simplifying complex cross-platform trust models, and driving security-critical migrations across dozens of teams.”

“Front-end/product engineer with strong financial-domain experience, including browser-based interfaces for retail planning, sales forecasting, and high-throughput trading data. Stands out for combining UI engineering with machine learning, time-series prediction, browser performance optimization, and functional programming across tools like React, TypeScript, Elm, OCaml, and Scala.”

“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.”

“Early-stage full-stack engineer who built Dokai's core web spreadsheet product and key AI features with just a two-engineer team. They combine strong product ownership with practical LLM integration experience, including reducing onboarding from a week to five minutes and solving difficult reliability and memory issues in production.”