Vetted Data Warehousing 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.”

Akshitha Singireddy

Screened

Junior Software Engineer specializing in data engineering and computer vision

Bellevue, WA1y exp

“Former Amazon intern who owned an end-to-end computer vision system to detect package anomalies in fulfillment centers, from data collection/labeling to production deployment on AWS (EC2/S3) with a Streamlit live-monitoring dashboard. Also has ML-in-production experience deploying and updating a recommendation model on Kubernetes (Minikube) with CI/CD via GitHub Actions, plus prior SDE experience with Jenkins-based pipelines and on-prem to AWS migration work using Glue.”

Sergey Pustovit

Screened

Director-level Data Platform & Analytics Engineering Leader specializing in distributed systems

Irvine, CA31y exp

“Entrepreneurially minded builder focused on proving architecture concepts via minimal demo prototypes for marketing. Has hands-on experience improving an A/B experimentation framework by interviewing stakeholders, identifying system limits and bottlenecks, and defining success criteria to scale experimentation and speed up analysis.”

“Technology/architecture leader with Accenture experience delivering data- and AI/ML-driven products, including a legal contract search solution and customer sales analytics for AWS. Known for scaling distributed teams (onshore/offshore), making pragmatic architecture decisions, and solving hard data problems (proprietary sources, data quality) while implementing scalable integrations like Redshift-to-Salesforce via parallelized pipelines.”

“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.”

“Technology/engineering leader with experience at Real Messenger, Wolters Kluwer, and Accenture AI, spanning roadmap definition through execution and org scaling. Has operated at the executive level (fundraising, investor relations, SPAC merger activities, media presentations) while driving architecture decisions validated by PoC/testing/production success metrics.”

Paul Kasinski

Screened ReferencesStrong rec.

Executive CIO/CTO specializing in enterprise transformation across retail, e-commerce, and AI

Santa Monica, CA17y exp

“Senior technology executive (CTO/SVP Technology, also board member) with experience modernizing legacy environments and scaling teams in high-growth and PE-owned contexts. Architected a standardized enterprise platform (ERP/WMS/CRM/POS/eComm/DWH/BI/integration) to rapidly migrate acquisitions—moving 7 companies in under 3 years and cutting migration timelines ~4x—while also driving major org redesign and hiring acceleration (30+ hires in 6 months).”

“Fractional CTO and AI/ML consultant at Clover Health with deep insurance domain experience (15 years as CTO/CISO/AI). Has spent significant time in PE/VC-backed environments (including Aquiline Capital Partners and Apollo Group), designing and engineering platforms while delivering against budgets, audits, and regulatory compliance. Recently helped build an insurance startup (2020–2025) and is now seeking a full-time role at a startup.”

“Explored a digital notarization startup concept in 2020 that stalled due to COVID-era inability to secure VC seed meetings; later saw the market validate the idea via a comparable acquisition (~$57M, per candidate). Now more interested in driving innovation and simplifying complex customer experiences within an established organization, using a highly structured, metrics-driven product execution approach.”

“Senior, product-focused engineer who has built real-time customer-facing web applications and a microservices backend (TypeScript/React/Node) using RabbitMQ, MongoDB, and Redis. Demonstrates strong operational maturity (idempotency, tracing/observability, backpressure) and built an internal console that became the primary tool for debugging, replaying jobs, and managing system behavior.”

“LLMOps-focused technical leader who took an LLM use case from prototype to production for a non-technical customer by combining trust-building and structured enablement with a robust AWS/Kubernetes-based MLOps stack. Built observability and rollback mechanisms (Grafana + MLflow) to troubleshoot in real time, and scaled delivery by hiring a 5-person team while partnering with sales to manage expectations and drive adoption across departments.”

Dennis Noto

Screened

Executive Technology & Security Leader specializing in FinTech, AI platforms, and enterprise modernization

Denver Metro Area36y exp

“Technology transformation leader who builds board-approved roadmaps and scales engineering orgs with strong Agile execution. Led large modernization efforts (e.g., Scottrade: 3,000 programs/4M LOC in 18 months) and scaled POCs into enterprise SaaS platforms using Docker, Kubernetes, Helm, and Terraform for high-concurrency workloads.”

Shant Mardigian

Screened

Executive Engineering Leader specializing in scalable streaming, media supply chain, and AI operations

19y exp

“Tech executive with Disney experience who has repeatedly scaled and restructured engineering organizations (from 4 to 30 and up to 100+), using OKRs/KPIs to drive business-aligned roadmaps. Hands-on with architecture and platform strategy, including adopting MongoDB Atlas to centralize transactional data and building shared core services (security/permissions, auditing, compliance) to increase product velocity across distributed teams.”

“Engineering/data platform leader from FLYR (airline ML forecasting and automated pricing) who built scalable ingestion/ETL and a canonical data model to onboard airlines with highly heterogeneous source systems. Created a golden-metrics layer for airline KPIs and implemented monitoring/backfill capabilities, cutting onboarding time by 50%+ while improving SLA performance and controlling cloud/ML training costs through stronger data quality gates.”