Design, build and manage scalable data pipelines using Azure Databricks; Develop ELT frameworks for ingesting and transforming structured and semi-structured data from on-prem and cloud sources – including cloud based API’s; Implement robust DevOps pipelines for code versioning, testing, deployment and monitoring using Azure DevOps; Ensure pipeline performance, reliability and observability using tools like Azure Monitor and Log Analytics; Collaborate with BI teams to support Power BI datasets and ensure optimal data model performance; Automate environment setup, configuration and permissions using infrastructure-as-code where possible; Write modular, testable code in SQL, Python or PySpark and manage version control with Git; Support production operations, root cause analysis and performance tuning; Understand data sources and data relationship models. Advanced proficiency in Azure Databricks; Experience building and managing CI/CD pipelines in Azure DevOps for data solutions; Strong SQL and ELT experience; familiarity with schema design (e.g., star, snowflake, denormalized); Hands-on expertise with PySpark and Databricks notebooks, including Delta Lake workflows; Familiarity with Git, branching strategies and repository management within Azure Repos; Understanding of data security and privacy best practices in Azure (RBAC, managed identities, encryption); Experience with Power BI dataflows, datasets and refresh configuration (preferred); Familiarity with data cataloging and governance tools (e.g., Microsoft Purview) a plus; and.