Databricks Champion

Role overview

A principal architect role leading lakehouse and platform modernization engagements while serving as the primary technical voice in a strategic data platform partnership. The position blends hands-on architecture with client-facing work, equally comfortable designing governance patterns or running executive workshops. The role requires current Databricks Champion certification and a track record of production delivery across cloud, data, and emerging AI workloads.

Responsibilities

- Lead architecture for lakehouse implementations, platform migrations, and modernization programs with Azure as the preferred cloud - Design Delta Lake, medallion, and Unity Catalog patterns balancing performance, cost, and governance - Direct technical migration from legacy warehouses such as Teradata, Snowflake, or Synapse into modern lakehouse and BI ecosystems - Define standards for ingestion, orchestration, CI/CD, testing, observability, and FinOps - Architect for AI readiness, including feature pipelines, model serving, and generative or agentic use cases - Join discovery calls, run architecture workshops, and shape technical solutions for sales pursuits - Scope engagements and review statements of work for technical accuracy and commercial clarity - Build reusable accelerators, reference architectures, and playbooks - Serve as the primary technical liaison to the data platform partner, including co-sell activities - Mentor engineers and run internal enablement sessions

Requirements

- Current Databricks Champion certification in good standing, with a shareable credentials wallet - 10+ years in data engineering or architecture, including 4+ years of hands-on Databricks delivery - Production lakehouse experience covering Delta Lake, Unity Catalog, Workflows or Lakeflow, and Databricks SQL - Strong command of PySpark, SQL, data modeling, and performance tuning - Background designing for security, governance, lineage, and compliance in regulated industries - Cloud platform depth, ideally Azure, with working knowledge of AWS or GCP - Client-facing comfort from engineering teams to C-suite - Clear written and verbal communication across audiences

Nice to have

- Additional Databricks certifications such as Data Engineer Professional or Solutions Architect - Power BI and Microsoft Fabric experience - Hands-on work with MLflow, Mosaic AI, and generative or agentic workloads - Infrastructure as code and CI/CD for data platforms - Consulting background including scoping, estimation, and statement-of-work contribution

Benefits and work setup

- Work directly with clients, engineers, and AI specialists on measurable business outcomes - No H-1B visa sponsorship available - Equal opportunity employer