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Job Description
Structured overview of role & requirementsAbout This Role
Design and implement scalable, secure data pipelines using Azure Data Factory, Azure Databricks (Spark), and associated Azure cloud services like Blob Storage and Azure Functions.
Develop and maintain ETL workflows and data transformation code primarily in Python or similar languages while ensuring high code and data quality through performance tuning and testing.
Collaborate with DevOps for CI/CD pipeline management, troubleshoot cloud networking issues, and implement data governance and monitoring frameworks across the full development lifecycle.
Minimum Requirements
Experience required designing and implementing data pipelines on Azure using Azure Data Factory and Databricks.
Proficiency in Python or similar programming languages for ETL and data processing.
Hands-on knowledge of SQL and NoSQL databases; understanding of Object-Oriented Programming and ETL best practices.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Technical lead capable of handling end-to-end data engineering solutions in Azure cloud environments.
Strong practical experience with cloud-native development and DevOps tooling such as Azure DevOps for CI/CD.
Focused on scalable, modular, and maintainable data solutions aligning with architectural best practices and data governance.