Databricks Architect

This role keeps DataZymes' Databricks capability ahead of the curve. The candidate will track the platform closely, sandbox new features before they're asked for, advise on internal POCs, and shape the standards and accelerators the wider practice builds on.

• Maintain deep, current expertise across the full Databricks platform including engineering (Delta Lake, DLT, Unity Catalog), deployment, cost optimization, governance, and the GenAI/agentic layer (Mosaic AI, Genie).

• Sandbox new features and form an independent view on their trade-offs before recommending them.

• Own cost optimization as a standing discipline — know what drives DBU spend and architect around it.

• Track Databricks' roadmap and releases, and translate them into what DataZymes' capability and accelerators should look like next.

• Recommend and scope internal POCs tied to real capability needs, not technology for its own sake.

• Challenge existing architecture and accelerators when the platform has moved on.

• Turn successful POCs into reusable patterns and reference architectures.

• Act as the internal reference for what's currently possible on Databricks.

• Contribute to architecture reviews as the platform-currency voice.

• Represent DataZymes' platform thinking externally where relevant — write-ups, talks, partner content.

• Shape Databricks standards and accelerators based on where the platform is heading.

• Guide certification and enablement priorities for the wider team.

• Feed platform and roadmap insight into DataZymes' Databricks partnership conversations.

• Databricks: Delta Lake, Unity Catalog, Delta Live Tables, Auto Loader, Databricks SQL, Workflows, cluster policies, deployment architecture.

• Cost & Ops: DBU cost modeling, cluster policy design, FinOps.

• GenAI Layer: Mosaic AI, Genie Spaces, AI/BI Dashboards, agent frameworks, MLflow.Agentbricks

• Cloud: working knowledge of Databricks on AWS, Azure, or GCP.