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. #J-18808-Ljbffr