
Databricks Platform Administrator
Department:Consulting
Type:ON-SITE
Region:Sidney
Location:Sydney, New South Wales, Australia
Experience:Associate
Estimated Salary:A$130,000 - A$170,000
Skills:
DATABRICKSAPACHE SPARKUNITY CATALOGDELTA LAKEPYTHONSQLAZUREAWSGCPCI/CDGIT
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Job Description
Posted on: June 1, 2026
Role: Databricks Platform AdministratorEmployment Type: ContractLocation: SydneyRole Overvie
wWe are seeking an experienced Databricks Platform Administrator to manage, support, and optimize enterprise Databricks environments. The role focuses on platform administration, security, governance, performance, automation, and operational support across data engineering, analytics, and AI workloads
. Key Responsibiliti
- esAdminister Databricks workspaces, clusters, jobs, workflows, and platform configuration
- s.Manage platform security, access controls, IAM integration, secrets, and Unity Catalo
- g.Monitor platform performance, availability, and cost optimizatio
- n.Troubleshoot Spark workloads, job failures, and platform issue
- s.Support Delta Lake, cloud storage integrations, and Lakehouse architecture
- s.Implement CI/CD processes and platform automation using APIs, CLI tools, and scriptin
- g.Collaborate with Data Engineering, Data Science, Cloud, Security, and MLOps team
- s.Provide production support and participate in incident resolution activitie
s. Required Skills & Experie
- nce5+ years of experience administering enterprise data or analytics platfor
- ms.Strong hands-on experience with Databricks administration and Apache Spa
- rk.Experience managing Databricks clusters, jobs, workflows, autoscaling, and security contro
- ls.Hands-on experience with Unity Catalog, Delta Lake, and data governan
- ce.Strong knowledge of Azure, AWS, or GCP cloud platfor
- ms.Proficiency in Python, SQL, and scripting/automati
- on.Experience with Git-based CI/CD process
- es.Strong troubleshooting, analytical, and communication skil
ls. Nice to
- HaveDatabricks certificat
- ion.Experience supporting ML/AI worklo
- ads.Experience with Kafka, Spark Streaming, or Terraf
orm.
Originally posted on LinkedIn
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