Principal Databricks Architect

We're looking for a Principal Databricks Architect to lead lakehouse and platform modernization engagements while serving as Nimble Gravity’s primary technical voice in our Databricks partnership. This role sits at the intersection of deep technical architecture and client-facing strategy — equally comfortable designing Unity Catalog governance patterns as leading an executive workshop or shaping a scope of work.

The ideal candidate has spent years architecting production Databricks implementations and knows how to translate that depth into business outcomes: scoping engagements with commercial clarity, flagging delivery risk before it becomes a problem, and mentoring the engineers who build alongside them. A current Databricks Champion certification and a track record of hands-on delivery across cloud, data, and emerging AI workloads are essential to doing this work credibly.

What You Will Do

Architect and deliver

• Lead architecture for lakehouse implementations, platform migrations, and modernization programs on Databricks (Azure preferred).
• Design Delta Lake, medallion, and Unity Catalog patterns that balance performance, cost, governance, and speed to value.
• Own technical direction for migrations from legacy platforms (for example Teradata, Snowflake, Synapse, or on-prem warehouses) into Databricks and Fabric/Power BI ecosystems.
• Define standards for ingestion, orchestration, CI/CD, testing, observability, and FinOps.
• Architect for AI readiness, including feature pipelines, Mosaic AI, model serving, and GenAI and agentic use cases built on governed data.

Support the sales pipeline

• Join discovery calls, run architecture workshops, and shape technical solutions for Databricks opportunities.
• Scope engagements and review SOWs for technical accuracy, risk, and commercial clarity.
• Build reusable accelerators, reference architectures, and playbooks so every pursuit and engagement starts ahead.

Strengthen the Databricks partnership

• Serve as Nimble Gravity’s primary technical liaison to Databricks, including partner program activities, co-sell motions, and field engagement.
• Maintain certification currency and help the wider team grow their Databricks credentials.
• Represent Nimble Gravity through client briefings, webinars, and Databricks events where it makes sense.
• Maintain awareness of Databricks features and technical roadmap.

Lead with judgment

• Ability to work with business stakeholders and translate business goals into practical technical roadmaps that executives can follow.
• Flag delivery risks early, including scope gaps, data quality issues, security concerns, and cost drivers, and propose a path forward.
• Mentor engineers and run internal enablement sessions.
• Partner with engagement leads and project managers to keep delivery on scope, on time, and on budget.

What You Bring

Required

• A current Databricks Champion certification, in good standing.
• A shareable link to your Databricks credentials wallet showing all active certifications. We will verify credentials before an offer is finalized.
• 10+ years in data engineering or data architecture, with 4+ years of deep, hands-on Databricks experience.
• Proven delivery of production lakehouse implementations, including Delta Lake, Unity Catalog, Workflows or Lakeflow, and Databricks SQL.
• Strong command of Spark (PySpark and SQL), data modeling (dimensional, data vault, or lakehouse patterns), and performance tuning.
• Experience designing for security and governance: access controls, lineage, PII handling, and compliance needs in regulated industries.
• Cloud platform depth, ideally Azure (ADLS, Entra ID, networking, DevOps), with working knowledge of AWS or GCP.
• Comfort in front of clients, from technical teams to C suite.
• Clear written and verbal communication. You can explain a tradeoff to an executive and then go deep with an engineer.

Strongly preferred

• Additional Databricks certifications (Data Engineer Professional, Solutions Architect, or equivalent).
• Experience with tools like Power BI and Microsoft Fabric.
• Hands-on work with MLflow, Mosaic AI, and GenAI or agentic workloads.
• Infrastructure as code (Terraform, Asset Bundles) and CI/CD for data platforms.
• Consulting or professional services background, including scoping, estimation, and SOW contribution.