Data Engineer - Databricks

What you will be doing:

• Act as Databricks Workspace Administrator, managing platform operations at scale
• Manage workspace governance, including access controls, cluster policies, job permissions, and cost/usage controls
• Design, create, and maintain Unity Catalog structures (catalogs, schemas, tables, and views)
• Implement and maintain permission models aligned to governance and compliance standards
• Manage identity and service principals, including least-privilege access models
• Support CI/CD, automation, and non-human identity integration across platforms
• Onboard and support tenant teams across analytics, ML, and GenAI workloads
• Run enablement sessions and provide guidance on best practices for Databricks usage
• Troubleshoot platform configuration and access issues
• Develop and maintain platform monitoring, dashboards, and alerting solutions
• Support SQL-based reporting and dashboard development within Databricks
• Maintain runbooks, documentation, and platform standards
• Drive automation, standardisation, and continuous platform improvement
• Support Hive/Glue and JDBC data pipeline setup and maintenance within Databricks

What we are looking for:

• Relevant Degree or Diploma in Computer Science, Information Technology, Data Engineering, or related field
• 4+ years’ industry experience in data engineering or platform engineering environments
• 2+ years’ hands-on experience as a Databricks Workspace Administrator
• Experience managing users, groups, and service principals (least-privilege access models)
• Strong understanding of data engineering, analytics, and AI/ML workloads
• Experience working in enterprise or regulated environments with strong governance requirements
• Strong SQL skills and experience with dashboard development/maintenance
• Experience with Hive/Glue and JDBC data pipeline setup and maintenance
• Strong communication skills and ability to engage with multiple stakeholder/tenant teams
• Understanding of cloud data platform concepts (AWS or Azure)

Advantageous:

• Experience supporting ML and Generative AI workloads on Databricks (e.g., RAG, model serving, evaluation workflows)
• Experience integrating Databricks with CI/CD and automation pipelines
• Exposure to platform engineering standards, templates, and self-service onboarding models
• Cloud platform experience (AWS or Azure)

Please note if you do not hear from us within 3 weeks, please consider your application unsuccessful.

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