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Data Support Engineer at 247Hire – Chicago | Jobyssey

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Data Support Engineer

247Hire · Chicago · 5 months ago

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Category: Support

airflow analytics automation azure azure-data-factory azure-devops ci-cd cloud data-analytics data-engineering data-governance data-lake data-pipelines data-quality

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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 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 +5

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).