Databricks Data Engineer

Azure Data EngineerRequired Skills & Experience: 6+ years of hands-on expertise with Azure Databricks, Python, PySpark, and Delta Lake. 6+ years of proven experience with Azure Data Factory for orchestrating and monitoring pipelines. Strong T-SQL Coding! There will be a coding exercise on interview. Strong SQL Server / T-SQL experience with a focus on query optimization, indexing strategies, and coding best practices. Demonstrated experience in SSIS package design, deployment, and performance tuning. Hands-on knowledge of Unity Catalog for governance. Experience with Git (Azure DevOps Repos) and CI/CD practices in data engineering projects.Nice to Have Skills & Experience: Microsoft Certified: Azure Data Engineer Associate (DP-203) Microsoft Certified: Azure Solutions Architect Expert or equivalent advanced Azure certification Databricks Certified Data Engineer Associate or Professional Additional Microsoft SQL Server or Azure certifications demonstrating advanced database and cloud expertiseJob Description: Data Pipeline Development: Design, build, and optimize ETL/ELT pipelines using Azure Databricks (PySpark, Delta Lake) and Azure Data Factory (ADF). Data Flows & Transformations: Develop pipelines, data flows, and complex transformations with ADF, PySpark, and T-SQL for seamless data extraction, transformation, and loading. Data Processing: Develop Databricks Python notebooks for tasks such as joining, filtering, and pre-aggregation. Database & Query Optimization: Optimize database performance through SQL query tuning, index optimization, and code improvements to ensure efficient data retrieval and manipulation. SSIS & Migration Support: Maintain and enhance SSIS package design and deployment for legacy workloads; contribute to migration and modernization into cloud-native pipelines. Collaboration & DevOps: Work with cross-functional teams using Git (Azure Repos) for version control and Azure DevOps pipelines (CI/CD) for deployment. Data Governance & Security: Partner with governance teams to integrate Microsoft Purview and Unity Catalog for cataloging, lineage tracking, and role-based security. API & External Integration: Implement REST APIs to retrieve analytics data from diverse external data feeds, enhancing accessibility and interoperability. Automation: Automate ETL processes and database maintenance tasks using SQL Agent Jobs, ensuring data integrity and operational reliability. Advanced SQL Expertise: Craft and optimize complex T-SQL queries to support efficient data processing and analytical workloads.