Chief Lakehouse Architect - Databricks CoE

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

Requirements

• 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
• 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

Additional Information

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.

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Company Intel

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