Vetted Power BI Professionals

“ML/backend engineer with PayPal experience building high-stakes production systems, including a GenAI internal support assistant and a real-time fraud scoring pipeline. Strong in Python/FastAPI, model-serving infrastructure, RAG architecture, and production observability, with clear readiness to transition those backend patterns into a TypeScript stack.”

“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”

“GTM/Revenue Operations-style leader who rebuilt a company’s go-to-market motion at IFS Loops while running cross-functional execution across Sales, CS, Product, and Marketing. Implemented an executive operating system (cadences, Notion dashboards, decision logs, briefing packets) that cut urgent escalations ~40% and freed 20–30% of CEO/CRO time, while delivering a pricing launch that drove >10% ACV uplift and improved activation/retention.”

“CTO-level technology leader with experience building end-to-end tech strategy and roadmaps, modernizing legacy environments in healthcare (GenesisCare), and scaling engineering into large global teams (Amadeus). Built a DevOps organization at Syniverse for the Visibility Suite, implementing Kubernetes/Terraform/Chef automation that drove ~75% faster deployments, and is known for staying hands-on (including data center work) while leading strategically.”

“Data engineer focused on large-scale ETL/ELT pipelines across cloud stacks (GCP and AWS), including Spark-based transformations and orchestration with Airflow. Has experience loading up to ~2TB per BigQuery target table and designing atomic loads to multiple downstream systems (Elasticsearch + Kafka), with Kubernetes deployment and Jenkins CI/CD.”

“Data engineer with experience at Bloomberg, UBS, and Bank of America building high-volume financial data platforms and services. Owned an end-to-end pipeline processing ~150–200M records/day (Kafka/Cassandra/S3 → Spark/PySpark → Snowflake) with strong data quality controls and Airflow reliability practices, reporting ~99% reliability and major performance gains. Also built large-scale external API ingestion with compliance-minded rate limiting, schema versioning, and quarantine/validation layers.”

Utkarsh Jain

Screened

Junior Private Equity & Credit Associate specializing in real estate private credit

San Francisco, CA2y exp

“Venture sourcing and pipeline operator with experience at HP Tech Ventures, sourcing startups across the US, Europe, and MENA and advancing select DeepTech opportunities to investment committee. Also supported a $500M roll-up acquisition strategy by sourcing 120+ private credit platforms, using research-driven, personalized outbound and structured pipeline tracking to move quickly into diligence.”

“Built a production GenAI support agent at Amazon for FBA on-call operations, using Bedrock, Lambda, RAG, and confidence-based human fallback to safely automate ticket triage. The system materially reduced ticket volume and manual workload while improving MTTR, showing strong depth in reliable LLM agent architecture under real operational constraints.”

“Cross-functional marketing/media operations leader with experience orchestrating multi-agency, full-funnel ways-of-working for a large P&G client. Built a client Power BI performance dashboard with an offshore AI team to eliminate manual data stitching and enable near real-time reporting, and regularly drives on-time/on-budget delivery through RACIs, Gantt-based ownership, and centralized status tracking.”

Daniel Bernhard

Screened

Director-level Manufacturing Operations leader specializing in electromechanical, MEMS, and biotech production

Emeryville, CA11y exp

“Operations/manufacturing leader who owned post-acquisition integration end-to-end, including site consolidation, technical transfer, and business systems alignment—delivering a 15-month multimillion-dollar program on time and 10% under budget. Experienced scaling a company from ~30 people to ~10x growth and driving public-company operational readiness; partnered with the CAO and external auditors to improve controls and remove quarterly shutdowns, increasing manufacturing capacity ~10% without added headcount.”

Arnell Dandridge

Screened

Director of Talent Acquisition & People Operations specializing in global hiring and HR systems

Remote9y exp

“Global recruiting leader at a startup who manages up to 20 recruiters worldwide while personally owning executive searches. Known for fast, high-impact hiring (e.g., EVP Customer Success filled in ~21 days) and for building practical, low-cost recruiting operations improvements—contract-to-hire strategy with CFO, global scheduling governance with CEO support, and HRBP-led onboarding engagement to prevent post-offer drop-off.”

“Analytics candidate with strong product and growth analytics experience across SQL, Spark, Python, and Tableau. They have built clickstream funnel pipelines, automated Bayesian experiment evaluation, and used Markov chain journey modeling to uncover onboarding friction that led to a 5% conversion improvement. They also show strong cross-functional influence by standardizing churn definitions across product and marketing teams and operationalizing adoption in shared dashboards.”

“Backend engineer who built and iterated a secure, multi-tenant RAG system over a large document corpus, emphasizing strict RBAC/ACL isolation, hybrid retrieval (vector+keyword), reranking, and strong observability to balance relevance, latency, and cost. Also led production refactors/migrations using strangler + feature flags/dual writes and has experience catching subtle real-world failure modes (including in a sensor calibration optimization pipeline).”

“ML/AI engineer focused on production-grade model reliability: built a monitoring and validation framework to detect drift, trigger anomaly alerts/retraining, and maintain consistent performance for device intelligence workflows at scale. Strong MLOps background with Python pipelines, Docker/Kubernetes deployments, Airflow orchestration, and real-time monitoring dashboards; experienced partnering with product managers to deliver business-facing insights.”

“Analytics professional with experience at McKinsey & Company and Dell Technologies, focused on turning messy operational and business data into trusted dashboards and decision tools. They combine SQL, Power BI, and Python to solve data quality issues, define metrics like retention, and deliver measurable impact such as a roughly 30% reduction in manual reporting time.”

“Compensation and payroll professional with hands-on ownership of end-to-end U.S. payroll and compensation cycle support. Stands out for using compa-ratio, market benchmarking, and Excel-based reconciliation tools to catch data issues, influence salary decisions, and strengthen payroll controls.”

“Growth creative lead at Amazon who ran structured, incrementality-informed A/B tests for Prime acquisition on Amazon DSP. Produced a winning benefit-led video + social-proof framework that improved CTR/CVR while cutting CPA (-24%) and increasing ROAS (+32%), then scaled the approach across email and onsite placements for an additional 10–12% lift in Prime sign-ups.”

“Technology leader with experience owning enterprise roadmaps and executing large-scale platform standardization during rapid M&A—most notably driving a tech roadmap across a 37-company portfolio at Regent, tackling technical debt and security gaps via unified cloud-native architecture, IAM/logging, CI/CD, and a global SRE model. Previously scaled an Adobe engineering org from 8 to 40+ across four regions, implementing clear org design, KPIs, and an extreme-ownership culture to support 24/7 operations and enterprise needs.”