Chief Lakehouse Architect – Databricks CoE

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