The Databricks Engineer will design, develop, and optimize large-scale data pipelines using Databricks and Azure cloud services. This role requires advanced expertise in Spark/PySpark, Delta Lake technologies, data governance, and cloud-based data engineering. The engineer will collaborate with cross-functional teams to deliver scalable, reliable, and high-performance data solutions that support analytics, BI, and business initiatives. Key Responsibilities Build and maintain scalable ETL/ELT data pipelines using Databricks. Use PySpark/Spark and SQL to process, cleanse, and transform large datasets. Integrate data from diverse sources such as Azure Blob Storage, ADLS, and relational/non-relational databases. Work with teams across the organization to prepare data for BI dashboards and reporting tools. Partner with business stakeholders to understand requirements and deliver tailored data solutions. Performance & Optimization Optimize Databricks workloads for performance, scalability, and cost efficiency. Monitor, troubleshoot, and resolve issues in data pipelines to ensure accuracy and reliability. Governance & Security Implement data governance, access controls, and security frameworks using Unity Catalog. Ensure compliance with enterprise data policies and regulatory standards. Deployment Use Databricks Asset Bundles for deploying jobs, notebooks, and configurations across environments. Maintain version control for Databricks artifacts and collaborate with the team on development best practices. Required Qualifications 10+ years of overall experience in data engineering. Recent experience in financial services, banking, or capital markets. Strong expertise in Databricks, including: Unity Catalog Lakehouse Architecture Table Triggers Databricks Runtime Proficiency with Azure cloud services. Deep understanding of Spark and PySpark for big data processing. Strong programming skills in Python. Experience with relational databases. Knowledge of Databricks Asset Bundles and GitLab for version control. Preferred Qualifications Familiarity with advanced Databricks Runtime configurations. Experience with streaming frameworks such as Spark Streaming. #J-18808-Ljbffr