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Tier-1 brand, metro location, mid-level generalist data engineer role with common platform skills.
Platform-specific Azure Databricks and Fabric skills moderate industry transferability, not widely generic.
Mandatory DP-203 and Databricks certifications plus specific Azure/PySpark expertise enforce strict technical filters.
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Design, develop, and implement data pipelines and integration solutions primarily using Azure Data Factory, Azure Databricks, and Azure Fabric to enable efficient data processing and analysis.
Develop complex PySpark and Python scripts for data transformation and analysis within cloud environments like Azure Synapse and Azure Analysis Services.
Manage source control and continuous integration/deployment pipelines using technologies such as GitHub and Azure DevOps.
4 to 8 years total work experience with minimum 3 years in relevant data engineering roles.
Bachelor’s or Master’s degree in Engineering, Technology, or MCA (B.Tech, M.Tech, M.E, B.E, MCA).
Must hold DP-203 Azure Data Engineer Associate and Databricks Certified Data Engineer Professional certifications.
Proven expertise in Azure Data Factory, Azure Databricks (advanced), Azure Fabric, PySpark scripting, Python scripting (mandatory), SQLDB with complex stored procedures, and experience with source control tools like GitHub or Azure DevOps.
Experienced data engineer skilled in Azure cloud native data services with strong hands-on coding in PySpark and Python for complex data transformation use cases.
Capable of independently troubleshooting, debugging, and optimizing data pipelines and analytics workflows in a CI/CD environment.
Holds recognized certifications (DP-203, Databricks Data Engineer) indicating solid knowledge of Azure data engineering best practices and frameworks.