Databricks Engineer

This role focuses on building, configuring, and supporting Databricks environments and data/analytics pipelines on cloud platforms (Azure, AWS, GCP). It involves translating technical designs into implementation tasks, supporting platform configuration, and troubleshooting issues for data science and client teams. The role is part of the AI & Engineering practice, specifically the AI & Data team, which helps clients scale analytics and AI capabilities.

What you'd actually do

  1. Build, configure, and support Databricks environments across Microsoft Azure, Amazon Web Services, and Google Cloud Platform, including integrations
  2. Develop and maintain Databricks notebooks, jobs, workflows, and pipelines for data and analytics solutions
  3. Translate approved technical designs into implementation tasks and document configuration, dependencies, and deployment steps
  4. Support platform configuration, infrastructure setup, testing, and deployment readiness across environments
  5. Work with delivery teams, data science teams, and client stakeholders to troubleshoot issues, support releases, and maintain platform performance

Skills

Required

  • Databricks platform implementation, configuration, or development
  • Building Databricks environments in Microsoft Azure, Amazon Web Services, or Google Cloud Platform, including integrations
  • Developing or supporting extract, transform, and load (ETL) pipelines in Databricks
  • Databricks workspace administration, machine learning operations (MLOps), or infrastructure setup

Nice to have

  • Experience in consulting
  • Experience serving healthcare industry clients