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