Chief Lakehouse Architect – Databricks CoE1
Principal architect responsible for defining and executing enterprise-grade Databricks Lakehouse architecture standards, engagements and guiding complex solution designs. Drive cost optimization and financial governance for Databricks platforms across clients and internal workloads.
Key Responsibilities
- Define Databricks reference architectures (batch, streaming, ML, GenAI)
- Own standards for Delta Lake, medallion architecture, Unity Catalog
- Design multi-workspace Databricks platform architectures
- Lead Databricks migrations from legacy data warehouses programs
- Design, Review and approve architecture for all Databricks deals
- Mentor architects and senior Databricks engineers
- Define Databricks FinOps framework
- Optimize cluster policies, DBU usage, and job scheduling
- Work with engineering teams on performance-to-cost optimization
- Advise leadership and clients on Databricks cost strategies
Experience
- 12–15 years in data architecture
- 5–7 years hands-on Databricks & Apache Spark
- 3+ years designing enterprise Databricks platforms, managing Databricks costs at scale
Skills
- Databricks platform internals & optimization
- Spark performance tuning and scalability
- Delta Lake internals (ACID, compaction, Z-order)
- Databricks Jobs, Workflows, CI/CD, IaC
- Cloud-native Databricks (AWS / Azure / GCP)
- Cluster tuning & auto-scaling strategies, Databricks DBU model & pricing
- Cloud billing & monitoring tools
- Cost optimization patterns for Spark workloads
Certifications (Preferred)
- Databricks Data Engineer Professional
- FinOps Practitioner
