Data Support Engineer
247Hire
A Data Application Support role specializing in Databricks focuses on maintaining, troubleshooting, and optimizing Spark-based data pipelines and Lakehouse architectures. Key responsibilities include resolving L2/L3 production incidents, performance tuning SQL/Python (PySpark) jobs, managing Delta Lake assets, and collaborating with data engineers to ensure data reliability. Key Responsibilities Incident & 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 DataFactory/Delta Live Tables), ensuring data quality and lineage (UnityCatalog). 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. Required Qualifications & Skills Technical 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 Skills Data 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). #J-18808-Ljbffr 247Hire
Vacancy posted 6 days ago
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