Senior AI Platform Ops Engineer

Join an enterprise data and AI platform team where you’ll drive the onboarding of new teams, data domains, and workloads onto a Databricks platform on AWS. In this senior, hands-on role, you’ll set the technical patterns others follow-building secure integrations to external data sources, establishing Unity Catalog governance at scale, operationalizing Databricks-native AI capabilities (including Genie and Mosaic AI), and implementing cost attribution practices that enable smarter engineering decisions. This is an individual contributor role with meaningful technical leadership and cross-functional influence.

• Databricks production administration (Unity Catalog, Delta Lake design, cluster configuration, job orchestration)
• Python + SQL + PySpark for reliable, scalable pipeline development
• AWS platform fundamentals (IAM, S3, VPC) and ability to contribute to Terraform
• Data governance implementation at scale (metadata standards, classification, lineage)
• Platform operations and cost attribution/chargeback for usage-based environments

Nice to Have Skills

• Databricks-native AI experience (Genie, Mosaic AI) or similar platform AI tooling
• LLM enablement experience (RAG, vector search, agent frameworks, LLM-driven workflows)
• CI/CD for Databricks deployments (Terraform, Asset Bundles, GitLab)
• Databricks certifications (Data Engineering, Platform Administration, Machine Learning)
• FinOps familiarity (cost allocation reporting, optimization practices)

Preferred Education and Experience

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related technical field (or equivalent practical experience)
• 5+ years in data engineering, platform engineering, or cloud data roles
• 3+ years of hands-on Databricks production environment management

Other Requirements

• Must be willing to participate in at least one in-person interview