Databricks Architect

About

We’re partnering with a leading enterprise to hire a Databricks Architect who will own the design and buildout of a next-gen data platform from the ground up.

This is not a pipeline role. This is full ownership of the Databricks ecosystem — architecture, performance, governance, and scale.

If you’ve been the person people go to when Databricks gets complex, keep reading.

What you’ll do:

• Architect end-to-end Databricks environments across dev, test, and prod
• Design scalable Lakehouse architecture using Delta Lake
• Implement Medallion architecture (Bronze, Silver, Gold) at scale
• Build and optimize high-performance Spark pipelines (batch + streaming)
• Own governance using Unity Catalog (access control, lineage, compliance)
• Drive performance + cost optimization (Photon, partitioning, autoscaling)
• Stand up CI/CD pipelines and infrastructure as code (Terraform, etc.)
• Integrate across AWS, Azure, or GCP ecosystems

What we’re looking for:

• 10+ years in data engineering / platform architecture
• Deep hands-on Databricks experience (not just exposure)
• Strong SQL + Python (PySpark or Scala)
• Experience with Delta Lake, Unity Catalog, and Medallion architecture
• Cloud experience (AWS, Azure, or GCP)
• CI/CD + orchestration (Airflow or similar)

Nice to have:

• Databricks certifications
• ML pipelines / MLflow
• Kafka or event-driven systems

Why this role:

• High-impact architecture ownership
• Fast interview process
• Contract-to-hire path (3–6 months)
• Enterprise scale challenges (not toy problems)

If you’ve built or scaled a Databricks platform before, you’ll stand out immediately.