Databricks Architect

As the Databricks Architect, you are the technical authority for Lakehouse design and delivery across enterprise engagements. You balance architectural vision with hands-on execution and elevate the engineering quality of the teams around you.

You will partner closely with the Databricks field team shaping joint solutions, supporting co-sell pursuits, and occasionally participating in roadshows and partner events. The primary focus is delivery excellence; the GTM dimension adds strategic reach.

Key Responsibilities

• Architecture & Delivery: Design Databricks Lakehouse platforms using Delta Lake; define reference patterns for ingestion, transformation, and consumption layers.
• Data Engineering: Build and maintain batch and streaming pipelines with Python, PySpark, and SQL; implement data quality and validation frameworks.
• Governance & Security: Implement Unity Catalog in production — governance, lineage, auditing, access controls, and secure sharing.
• Performance & Cost: Optimize workloads end-to-end; establish cluster policies, tagging, and cost controls.
• Platform Standards: Drive CI/CD, environment promotion (dev/test/prod), and engineering best practices across teams.
• Operational Excellence: Define monitoring, alerting, incident response, and SLA/SLO processes; implement observability across pipelines.
• Technical Leadership: Mentor engineers, lead design and code reviews, and shape the practice roadmap.
• Partner Engagement: Collaborate with the Databricks partnership team on joint offerings, co-sell activity, and select roadshow and field events.

What You Bring

• 10+ years in data engineering or architecture, including 3+ years in technical leadership capacity.
• Databricks mastery: Delta Lake, Unity Catalog, Workflows/Jobs, performance tuning — in production environments.
• Advanced Python, PySpark & SQL with large-scale data processing and optimization experience.
• Cloud platform fluency on at least one major hyperscaler (AWS, Azure, or GCP) — IAM, networking, observability, cost management.
• CI/CD expertise for data platforms — testing, packaging, version control, and deployment automation.
• Stakeholder management skills with the ability to translate architecture into business outcomes for both technical and executive audiences.
• Databricks ecosystem awareness — familiarity with partner programs, joint GTM, and co-sell dynamics is a plus, not a prerequisite.

Ideal Candidate

An architect with a consulting or services background who has delivered Databricks platform programs end-to-end. You are hands-on, entrepreneurial, and ready to own delivery outcomes while building practice capability alongside you.

What Success Looks Like

• Reusable, production-grade architectures that clients trust and reference.
• Engineering standards measurably elevated across the practice.
• Credible presence in the Databricks partner ecosystem.
• A pipeline of reusable accelerators and documented patterns.