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
