Design, deploy, and support enterprise Databricks Lakehouse architecture. Implement Unity Catalog and global cluster policies, optimize Spark performance and storage, enforce RBAC and data masking, and productionize Databricks capabilities while enabling secure, cost-controlled data platform usage.
Role Overview
We are seeking a Senior Platform Engineer to design, secure, and optimize our enterprise data infrastructure. You will own the foundational architecture of our Databricks Lakehouse, ensuring data teams can build efficiently within a secure, high-performance, and cost-controlled ecosystem.
Key Responsibilities
- Infrastructure Management: Architecture, deployment, and daily support of enterprise Databricks Workspaces.
- Data Governance: Full implementation of Unity Catalog for data lineage and access control.
- Guardrails & Governance: Designing global cluster policies to balance user agility with cost.
- Performance Tuning: Optimizing complex Spark configurations, storage layouts, and query speeds.
- Innovation Delivery: Productionizing cutting-edge capabilities like Databricks Genie and Lakehouse Apps.
Required Technical Skills
- Data Platform: Advanced Databricks administration (Workspaces, Unity Catalog, Delta Lake).
- Cloud Infrastructure: Strong experience with AWS, Azure, or GCP via Terraform (IaC).
- Compute Optimization: Deep knowledge of Apache Spark internals and Spark UI tuning.
- Security & Compliance: Implementing Role-Based Access Control (RBAC) and data masking.
- CI/CD Pipelines: Building automated deployment tracks using Git, GitHub Actions, or GitLab CI.
Soft Skills & Qualifications
- Experience: 8+ years in Platform, DevOps, or Data Infrastructure Engineering.
- Collaboration: Ability to bridge the gap between Data Science teams and IT security.
- Problem Solving: Strong root-cause analysis skills for complex, distributed computing issues.
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