Vetted Power BI Professionals

Karan Mehta

Screened ReferencesStrong rec.

Director-level Business Operations & GTM Strategy leader specializing in analytics and performance

Foster City, CA9y exp

“ZS consultant/product owner who repeatedly turns vague GTM performance goals into decision-centric analytics products and operating rhythms. Has scaled analytics initiatives from pilots into $1M+ platforms with 100+ leader adoption, and tied measurement tools to material business outcomes (e.g., $10M+ incremental revenue impact) through change management and cross-functional alignment.”

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.”

kayla Battle

Screened

Senior Global Talent Acquisition Operations leader specializing in HRIS/ATS modernization and analytics

Plano, TX8y exp

“Talent Acquisition Operations leader with 8 years of experience owning global recruiting process strategy and TA technology. Led a global iCIMS ATS implementation and standardized recruiting workflows across 15 markets, partnering closely with finance, legal, L&D, and local HR teams to ensure compliance (including Egypt-specific labor law requirements) and enable cross-market recruiter support.”

Deekshit Myakala

Screened

Mid-level Software Engineer specializing in cloud automation and data/ETL platforms

Arlington, Virginia6y exp

“Backend engineer with AWS multi-region production experience building APIs and workflow automation for data center/storage hardware operations (firmware orchestration, maintenance checks, ticketing, dashboards). Also shipped an internal AI chat tool that parses hardware runbooks and incorporates user feedback to retrain the model, and has a strong testing/quality discipline (95%+ coverage) plus database performance tuning via indexing and query monitoring.”

“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.”

Michael Smith

Screened

Executive HR Business Partner specializing in global people experience and organizational transformation

New York, NY11y exp

“HR Business Partner with strong senior-leader partnership experience spanning org design/workforce planning, people analytics, and executive coaching. Has led high-impact retention and compensation strategies using attrition and market data, and managed complex employee relations matters including an ADA disability discrimination case through investigation and separation agreement.”

“Built and shipped a production agentic RAG system for healthcare analysts that automated compliance/operations knowledge retrieval across PDFs, reports, and databases. Emphasizes production reliability (monitoring, retries, fallbacks, async queues), strong evaluation/iteration loops, and measurable impact (3–10s responses and ~98% top-k retrieval accuracy).”

“Operations/program leader who partnered closely with a COO to drive transformation initiatives (compliance workflow automation and budgeting redesign), implementing governance cadences and executive dashboards to improve alignment and decision speed. Managed a $120MM operating budget and successfully delivered regulator-mandated resolution planning under tight timelines, while maintaining strict discretion during restructuring work involving sensitive HR data.”

“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.”

Dheeraj Kumar

Screened

Intern Data Scientist specializing in marketing analytics and data engineering

Tucson, Arizona2y exp

“AI/LLM practitioner with internships at Dell Technologies and Roche who built and deployed a healthcare-focused "Doctor LLM" by fine-tuning Meta Llama 3.2 on healthcaremagic.json, emphasizing safety guardrails to prevent harmful medical advice. Experienced in productionizing AI workflows with monitoring, testing, and orchestration (Airflow, Kubernetes), and in delivering AI-agent-driven competitive landscape insights to non-technical business stakeholders.”

Asrith Velireddy

Screened

Mid-level AI/ML Engineer specializing in MLOps, LLMs, and scalable ML systems

Harrison, NJ4y exp

“ML/LLM engineer at Adobe who deployed a transformer-based personalization and campaign-targeting recommender system end-to-end, including PySpark/Airflow pipelines processing 12M+ events/day and containerized inference on AWS SageMaker (Docker/Kubernetes). Also has hands-on LLM workflow experience (RAG, semantic search, prompt optimization, hallucination mitigation) with a metrics-driven approach to reliability, drift monitoring, and reproducible retraining via MLflow.”

“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.”