• Design, build, and optimize data pipelines and workflows in Azure and Databricks, including Data Lake and SQL Database integrations. • Implement scalable ETL/ELT frameworks using Azure Data Factory, Databricks, and Spark. • Optimize data structures and queries for performance, reliability, and cost efficiency. • Drive data quality and governance initiatives, including metadata management and validation frameworks. • Collaborate with cross-functional teams to define and implement data models aligned with business and analytical requirements. • Maintain clear documentation and enforce engineering best practices for reproducibility and maintainability. • Ensure adherence to security, compliance, and data privacy standards. • Mentor junior engineers and contribute to establishing engineering best practices. • Support CI/CD pipeline development for data workflows using GitLab or Azure DevOps. • Partner with data consumers to publish curated datasets into reporting tools such as Power BI.