Databricks Architect
Summary
Architect role owning DataZymes' Databricks platform capability: tracking releases, sandboxing new features, running internal POCs, and shaping the standards and accelerators the practice builds on. Requires deep, current Databricks expertise (Delta Lake, Unity Catalog, DLT, Mosaic AI/Genie), cost-optimization discipline, multi-cloud exposure, and a Professional-level certification.
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
ROLE OVERVIEW
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.
KEY RESPONSIBILITIES
Platform Mastery
• 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.
Roadmap & Innovation
• 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.
Technical Advisory
• 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.
Practice Influence
• 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.
WHAT WE ARE LOOKING FOR
Must-Have
• 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).
TECHNICAL STACK
• 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.