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Strong PwC brand, mid-level generalist data role, Bangalore location, and common experience band increase applicant competition.
Azure Databricks and cloud-specific tooling make skills somewhat transferable but still domain- and platform-sensitive.
Mandatory certifications, specific Azure/Databricks skillset, and explicit 4–8 years requirement make filtering strict.
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Design and develop data pipelines, integration, and transformation solutions leveraging Azure Fabric, Azure Data Factory, Azure Databricks, Synapse, and Python/PySpark.
Troubleshoot and debug complex data engineering issues while managing source control using tools like GitHub and Azure DevOps with build and release pipelines.
Deliver robust data infrastructure enabling efficient data processing and analytics to generate actionable insights for client business growth.
4 to 8 years total work experience with minimum 3 years relevant experience in data engineering roles.
Mandatory technical expertise in Azure Data Factory, Azure Databricks, Azure Fabric, SQL Database (complex stored procedures), Python scripting, and PySpark scripting.
Certifications required: DP-203 (Azure Data Engineer Associate) and Databricks Certified Data Engineer Professional (Architect/Managerial level).
Educational qualification: Bachelor’s in Technology/Engineering (B.Tech/B.E) or Master’s in Technology/Engineering/MCA.
Experienced data engineer with proven skills in Azure cloud data services and advanced scripting for scalable data analytics.
Capability to independently develop, debug, and maintain enterprise-grade data pipelines and integrations using latest Azure technologies.
Comfortable working with source control, CI/CD pipelines, and following best practices in data platform development and deployment.