Platform Administrator (Databricks)
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Job description
We are looking for an experienced Platform Administrator (Databricks) for a long-term project. The customer is a company in California, an industry leader in the sale of tickets to events in Europe and the USA.
We offer 100% remote, full-time work.
Main tasks:
- Manage multiple Databricks workspaces (dev/qa/prod);
- Configure cluster policies, governance & compliance;
- Create & maintain unity catalog objects: catalogs, schemas, grants, service principals, external storage etc;
- Monitor and debug failed / long-running jobs using system tables (job_run_timeline, node_timeline, workflow_run);
- Troubleshoot cluster crashes, driver OOM, executor failures, memory leaks;
- Investigate Python / Spark errors, dependency conflicts (PyPI, WHL, Maven)
- Assist users with cluster/job configuration, notebook errors, unity catalog permissions;
- Explain platform limitations and best practices to Data engineers;
- Maintain confluence pages with platform rules & troubleshooting guides;
- Experience in implementation, integration or technical support;
- Experience with Linux, Bash;
- Confident SQL skills;
- Strong experience of working with AWS Infrastructure (ec2, s3, iam, vpc, secret management, sqs);
- Experience with Python sufficient for writing small scripts or applications;
- Experience of maintaining Databricks jobs & environments;
- Experience with REST API/SDK;
- Understanding of file-based databases (DeltaLake, Parquet, Hive);
- Understanding of of cluster types & node families;
- Spoken English at Intermediate level or higher;
- Databricks REST API / Databricks SDK;
- Working with schema evolution, time travel, vacuum, compaction, z-order;
- Debugging corrupted delta tables (conflicting commits, tombstones, missing checkpoints);
- Understanding of acidimplementationon top of object storage;
- Spark knowledge (jobs, partitions, queries), experience in Kafka or similar technology, familiarity with Terraform / Gitlab CI;
- Cost monitoring for platform services and objects;
- Experience in enterprise Data platforms;
- Remote work with no time trackers, flexible working hours
- Full-time (8 hours/day)
- Attractive USD compensation
- Paid vacation, holidays, sick leaves
Originally posted on Himalayas
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