Vetted Azure Synapse Analytics Professionals

Sai Anirudh Kondaveeti

Screened

Senior Software Engineer specializing in Azure cloud, identity, and networking

Redmond, WA7y exp

“Backend/cloud engineer with deep Azure and distributed-systems experience: owned an end-to-end Python multi-orchestrator config generator (Contrail) spanning OpenStack/vCenter/OpenShift/Kubernetes via a translation-layer approach. Built GitOps-style ARM-template infrastructure and CI/CD with automated testing, including a zero-downtime Databricks-to-Synapse migration using parallel production validation. Worked on Microsoft Azure Identity gateway (reverse proxy for auth) and executed ring-based deployments for major platform migration.”

“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.”

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.”

“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.”

“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.”