{"schemaVersion":"jobsearcher.job.v1","id":"33fd29be6d5a44a7581a6097","url":"https://jobsearcher.com/jobs/33fd29be6d5a44a7581a6097","canonicalUrl":"https://jobsearcher.com/jobs/33fd29be6d5a44a7581a6097","title":"Data Support Engineer (Databricks experience)","description":"Key ResponsibilitiesIncident & Problem Management: Provide L2/L3 support for data applications, resolving production issues and troubleshooting Databricks jobs, notebooks, and workflows.Performance Tuning: Optimize Spark applications, SQL queries, and Delta Lake tables to improve efficiency and reduce costs.Pipeline Maintenance: Monitor and troubleshoot ETL/ELT pipelines in Databricks (including Data Factory/Delta Live Tables), ensuring data quality and lineage (Unity Catalog).Collaboration: Act as a liaison between users, data engineering teams, and platform engineering, providing technical expertise and contributing to documentation.Automation: Create tools to automate routine support tasks and enhance support team productivity. Databricks +5Required Qualifications & SkillsTechnical Expertise: Strong hands-on experience with Apache Spark, Python/PySpark, and SQL.Databricks Ecosystem: Proficiency with Databricks Unified Data Analytics Platform, Delta Lake, and ideally Azure Databricks.Cloud Data Storage: Experience with Azure Data Lake Storage (ADLS Gen2) or similar data lake technologies.Version Control & CI/CD: Experience with Git/Azure DevOps for code management.Problem-Solving: Strong analytical skills, with the ability to diagnose complex data processing bottlenecks. \"Nice-to-Have\" SkillsData orchestration tools (e.g., Apache Airflow, Azure Data Factory).Data governance tools (e.g., Unity Catalog, Collibra).Streaming data knowledge (e.g., Spark Structured Streaming).","company":"Medix","rawCompany":"medix","city":"Chicago","state":"IL","isRemote":false,"isActive":false,"createdAt":"2026-04-29T04:47:09.215Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Support Engineer (Databricks experience)","description":"Key ResponsibilitiesIncident & Problem Management: Provide L2/L3 support for data applications, resolving production issues and troubleshooting Databricks jobs, notebooks, and workflows.Performance Tuning: Optimize Spark applications, SQL queries, and Delta Lake tables to improve efficiency and reduce costs.Pipeline Maintenance: Monitor and troubleshoot ETL/ELT pipelines in Databricks (including Data Factory/Delta Live Tables), ensuring data quality and lineage (Unity Catalog).Collaboration: Act as a liaison between users, data engineering teams, and platform engineering, providing technical expertise and contributing to documentation.Automation: Create tools to automate routine support tasks and enhance support team productivity. Databricks +5Required Qualifications & SkillsTechnical Expertise: Strong hands-on experience with Apache Spark, Python/PySpark, and SQL.Databricks Ecosystem: Proficiency with Databricks Unified Data Analytics Platform, Delta Lake, and ideally Azure Databricks.Cloud Data Storage: Experience with Azure Data Lake Storage (ADLS Gen2) or similar data lake technologies.Version Control & CI/CD: Experience with Git/Azure DevOps for code management.Problem-Solving: Strong analytical skills, with the ability to diagnose complex data processing bottlenecks. \"Nice-to-Have\" SkillsData orchestration tools (e.g., Apache Airflow, Azure Data Factory).Data governance tools (e.g., Unity Catalog, Collibra).Streaming data knowledge (e.g., Spark Structured Streaming).","datePosted":"2026-04-29T04:47:09.215Z","dateModified":"2026-04-29T04:47:09.215Z","hiringOrganization":{"@type":"Organization","name":"Medix","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Chicago","addressRegion":"IL","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"33fd29be6d5a44a7581a6097"},"url":"https://jobsearcher.com/jobs/33fd29be6d5a44a7581a6097"}}