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.Follow for the Latest Vacancies Join Psybergate Careers Channel here: