Senior Databricks Platform Engineer

Talentola; Edina (MN); On-site; USD 130,000 - 190,000; Full time

Job summary

Talentola in Edina, MN is seeking a Senior Databricks Platform Engineer to design, build, and scale an enterprise Databricks platform for analytics, ML, and AI initiatives.

You will work with Enterprise Architecture, Data Engineering, Cloud Engineering, Product Management, and Data Science to create reusable services, automation, standards, and self-service capabilities to boost adoption and developer productivity.

Qualifications

• 5+ years of relevant experience preferred.
• 2+ years hands-on with the Databricks platform required.
• Experience with Azure cloud services and cloud-native architectures preferred.
• Experience developing IaC solutions using Terraform and CI/CD pipelines.
• Strong knowledge of Delta Lake, Unity Catalog, Apache Spark, and lakehouse architectures.
• Experience with MLflow, MLOps, AI platform technologies, streaming, or event-driven architectures preferred.

Responsibilities

• Develop and enhance enterprise Databricks platform capabilities for analytics, data products, ML, and AI workloads.
• Implement platform architectures, engineering standards, and reusable design patterns.
• Build and maintain IaC solutions, CI/CD pipelines, and platform automation.
• Create reusable templates and deployment patterns to enable self-service platform adoption.
• Optimize platform scalability, performance, reliability, and cost efficiency across clouds.
• Collaborate with EA, Cloud Engineering, Data Engineering, Product Management, and Data Science teams.
• Support platform services including MLflow, Model Registry, and Feature Store.

Skills

Databricks

AI/MLOps

Plumini

Azure DevOps

Education

Relevant degree preferred

Tools

Azure DevOps

Job description

Talentola in Edina, MN is seeking a Senior Databricks Platform Engineer to design, build, and scale an enterprise Databricks platform for analytics, ML, and AI initiatives.

You will work with Enterprise Architecture, Data Engineering, Cloud Engineering, Product Management, and Data Science to create reusable services, automation, standards, and self-service capabilities to boost adoption and developer productivity.