Platform Administrator (Databricks)

Nitka Technologies•,

11d•Remote

About The Position

Nitka Technologies is seeking an experienced Platform Administrator (Databricks) for a long-term remote, full-time project. The client is a leading company in California specializing in ticket sales for European and US events. This role involves managing multiple Databricks workspaces, configuring policies, managing Unity Catalog, monitoring and debugging jobs and clusters, troubleshooting errors, and assisting users with platform-related issues. The administrator will also be responsible for maintaining documentation and explaining best practices to Data Engineers.

Requirements

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

Nice To Haves

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 acid implementation on 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

Responsibilities

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