Details
Job Description
Job Summary
We are looking for a Databricks Support Engineer to join our global platform support team. The successful candidate will be responsible for supporting enterprise data platforms built on Databricks and cloud technologies, helping users troubleshoot issues, investigate incidents, and ensure platform stability and reliability.
The ideal candidate has hands-on experience with Databricks, Spark, data pipelines, cloud platforms, and production support environments.
Key Responsibilities
- Provide L2/L3 support for Databricks-based data platforms.
- Investigate and resolve incidents related to data pipelines, workflows, clusters, and integrations.
- Troubleshoot PySpark, Spark SQL, ETL/ELT processes, and data processing jobs.
- Monitor platform health and proactively identify potential issues.
- Collaborate with engineering, platform, and product teams to resolve complex problems.
- Support cloud-native data solutions in AWS and/or Azure environments.
- Create and maintain technical documentation, runbooks, and knowledge-base articles.
- Participate in incident management, root cause analysis, and problem management activities.
- Contribute to platform improvements and automation initiatives.
Job Requirements
Required Skills & Experience
- Experience administering or supporting Databricks environments.
- Experience building or supporting data pipelines and ETL/ELT processes.
- Strong knowledge of Spark, PySpark, and SQL.
- Experience with AWS and/or Azure cloud services.
- Good understanding of data engineering concepts and distributed processing.
- Python programming skills.
- Strong troubleshooting and analytical skills.
- Excellent written and verbal communication skills in English.
Nice to Have
- Databricks certifications.
- Experience with Airflow, Azure Data Factory, AWS Glue, or similar orchestration tools.
- DevOps experience (Git, Jenkins, CI/CD, Containers).
- Experience working in ITIL-based support organizations.
- ServiceNow experience.
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