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Mid-level, popular Azure data role with broad skillset and metro location drives high competition.
Azure-specific data engineering skills transfer across industries but platform specialization raises moderate sensitivity.
Explicit 4–6 years plus mandatory Azure data stack and tooling increases filter strictness to high.
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Develop, implement, and manage data engineering solutions using Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and related Azure services.
Build and maintain data pipelines integrating source systems such as SQL Server, Oracle, SAP, REST APIs, and flat files.
Ensure security, monitoring, and CI/CD practices for data solutions using Azure Key Vault, RBAC, Git, and Azure DevOps/GitHub Actions.
4 to 6 years of experience in Azure Data Engineering.
Proficiency with Azure Data Factory, Azure Databricks (PySpark), Azure Synapse Analytics, and Azure Data Lake Storage Gen2.
Strong programming skills in Python (PySpark) and SQL/Spark SQL.
Bachelor’s degree in Computer Science, Information Technology, or related field.
Experience with dimensional modeling using Star and Snowflake schemas in data warehousing.
Familiarity with CI/CD tools like Git, Azure DevOps, and monitoring technologies like Log Analytics.
Comfortable working in Agile/Scrum environments with strong analytical and collaborative skills.