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Metro location, common Data Engineer role and broad Azure/Databricks/PySpark skills increase applicant density.
Cloud data pipeline and Databricks experience transfers across industries but requires specific platform expertise.
Mandatory 1–2 years, Azure Databricks/Data Factory/PySpark/Python skills and 24×7 shift raise screening strictness.
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Monitor and support 24×7 DataOps pipelines on Azure Data Factory and Azure Databricks ensuring SLA adherence and operational stability.
Troubleshoot and resolve failures in pipelines, Databricks jobs, Python/PySpark scripts, performing root cause analysis and implementing permanent fixes.
Support Power BI dataset refreshes and data validation, guide L1 engineers during incidents, and maintain operational documentation including runbooks and incident records.
Bachelor’s degree (4-year) or equivalent.
1–2 years of work experience in data pipeline support or development.
Hands-on experience with Azure Data Factory, Azure Databricks, and strong Python programming skills including OOP concepts.
Willingness to work in a 24×7 rotational shift model.
Experienced in operational support and troubleshooting of cloud-based data pipelines, especially Azure Data Factory and Databricks environments.
Skilled in Python, PySpark, and SQL with capability to analyze and fix production data workflow issues.
Comfortable working in a demanding 24×7 production environment with documented escalation and incident management processes.