Vetted BigQuery Professionals

“Backend/data engineer with strong authorization and compliance-domain experience: led a phased migration from a simplistic role model to modern RBAC on a Python serverless stack (Auth0 + AWS Lambda/API Gateway), coordinating changes across 5 repos with extensive manual and automated validation. Previously built and operated custom ETL pipelines (Airflow + Groovy/Java on Spark/YARN/Hadoop) to normalize messy customer email/chat/voice data for NLP-driven financial compliance indicators, including complex email journaling metadata enrichment and large-scale remediation reprocessing after production bugs.”

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.”

“Backend/data engineering candidate with Netflix experience designing and migrating analytics platforms from batch to real-time streaming (Kafka/Flink) across AWS and GCP. Delivered measurable improvements (40% lower data delay, 99.9% accuracy) using phased rollouts, automated data validation (Great Expectations), and strong observability (Prometheus/Grafana), and proactively hardened pipelines with idempotency to prevent duplicate Kafka processing.”

“Data engineer at Microsoft who owned an end-to-end subscription analytics platform processing 7TB+ daily across 40+ pipelines, combining ADF batch ingestion with Kafka/Spark streaming and rigorous Great Expectations quality gates. Built a Fabric-based self-service ingestion platform with CI/CD and observability, plus a Databricks feature store serving near-real-time ML inference with Delta Lake reliability and versioning.”

Adam Wermus

Screened

Senior Data Engineer & Render Tools Developer specializing in VFX and render farm pipelines

Santa Monica, CA7y exp

“Real-time simulation/physics engineer who optimized character effects and cloth for the "Infinity" game by implementing and profiling multiple ODE integrators, including pioneering the largely undocumented Parker-Sochacki method (optimized 5/7 sims; >30% speedup on a particle system). Also built SPH fluid solvers in Unity (C#) and created Grafana/Python Dash dashboards to analyze latency/throughput, with strong interest in applying math/physics and tooling to soccer/football gameplay.”

“Built GenMedX, a multi-module clinical AI system for emergency department decision support spanning triage prediction, diagnosis, medication Q&A, and visit summarization. Stands out for combining medical LLM fine-tuning, RAG, and rigorous evaluation/monitoring to drive a major triage recall improvement from 38.5% to 76.6%, with a strong focus on safety, edge-case detection, and production reliability.”

“Built a production internal knowledge assistant using a RAG pipeline over large spreadsheets, PDFs, and support documents, using transformer embeddings stored in FAISS. Focused on real-world production challenges—format normalization, retrieval quality, hallucination reduction (context-only + citations), and latency—using hybrid retrieval, quantization, and containerized deployment, and communicated the workflow to non-technical stakeholders using simple analogies.”

“ML/LLM engineer with production experience building a multi-GPU LLM inference platform using TensorRT and vLLM, achieving ~40% p95 latency reduction through batching/KV caching, quantization, and CUDA/runtime tuning. Also has end-to-end orchestration experience (Kubernetes, Airflow) and has delivered real-time fraud detection systems at Accenture in close collaboration with non-technical risk and product stakeholders.”

Chaithanya Konda

Screened

Mid-level Data Engineer specializing in multi-cloud analytics platforms

Waltham, MA6y exp

“Data engineer with hands-on GCP platform experience spanning BigQuery, Cloud SQL, Dataflow, and Cloud Composer, including both production operations and cloud migration work. They led a migration from legacy SQL Server/Oracle systems to a cloud-native BigQuery architecture and cite measurable impact: processing reduced from hours to minutes, query latency improved 60%+, and ingestion time improved 40%.”

“Software engineer with practical, day-to-day experience embedding AI into development workflows across coding, testing, code review, and AWS data pipelines. Uses tools like Claude, Cline, JUnit, Mockito, and Amazon Bedrock, and stands out for having a realistic, mature view of agent limitations, hallucinations, and the need for strong prompting and human validation.”

“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”