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.