Interview - Face to face Position Overview: Build and maintain scalable data pipelines using Azure Databricks to support DATA & AI ACDP projects. Apply 3-4 years of experience to deliver reliable ETL processes and collaborate on data-driven insights. Key Responsibilities: • Design, build, and optimize data pipelines in Azure Databricks for ingestion, ETL/ELT, and transformations, implementing Medallion Architecture (Bronze, Silver, Gold) with Delta Lake for data quality and versioning. • Utilize Databricks Spark (PySpark, SQL), Delta Live Tables, and Unity Catalog for pipeline development, governance, and basic streaming. • Integrate data from ADLS Gen2, Azure SQL Database, and SQL Pools; support orchestration via Databricks workflows. • Implement CI/CD in Azure DevOps for Databricks deployments, including Bicep templates and ADF integration. • Apply data quality measures (expectations, constraints), security (RBAC, encryption), and monitoring for performance/cost efficiency using auto-scaling and Photon. • Work with analysts and stakeholders to refine requirements into functional workflows; handle data cleansing, modeling, and Python/SQL scripting for structured/unstructured data. • Troubleshoot pipelines and contribute to documentation/best practices. Required Qualifications: • 8 years in data engineering, focused on Azure Databricks pipelines and ETL • Proficiency in PySpark, SQL, Python; experience with cloud storage and basic orchestration • Familiarity with Azure fundamentals and collaborative tools