Chief Lakehouse Architect – Databricks CoE

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