Databricks Architect

We are looking for passionate and driven professionals to join DataZymes, a next-generation analytics and data science company founded in 2016. At DataZymes, we focus on driving technology-led innovation and helping clients maximize the value of their data and analytics investments through cutting-edge platforms and consulting expertise. If you are excited about working on impactful solutions in the healthcare analytics space and want to be part of a high-performance, fast-growing team, we’d love to hear from you.
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.

•        6–9 years in data engineering or platform architecture, with deep, current Databricks expertise.

•        Breadth across engineering, deployment, cost optimization, and the GenAI/agentic layer.

•        Demonstrated habit of tracking releases and independently testing new features.

•        Comfortable forming and defending an independent technical opinion.

•        At least one active Databricks Professional-level certification.

•        First-principles mindset — more interested in the better way than the known way.

•        Experience scoping or running Databricks POCs that influenced a build decision.

•        Public or internal thought leadership on Databricks capability.

•        Familiarity with Databricks partner programme mechanics and roadmap briefings.

•        Exposure to multi-cloud Databricks deployments (AWS, Azure, GCP).

•        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.