Senior Data Engineer (Databricks)

<h3>Why Join Exadel </h3> <p>We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.</p> <p>From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.<br>What powers it all? Our people are ambitious, collaborative, and constantly evolving.</p> <h3>About the Client  </h3> <p>The health and fitness software and payment processing provider in the United States, Puerto Rico, Canada, and Mexico. Founded in 1981, they currently work with 7,000+ health clubs. Customer offerings include payment processing and gym management solutions that allow managers to track memberships and schedules and automate payment processing functions.</p> <h3>Project Team </h3> <p>Team composition: 4 Senior Data Engineers, 1 Project Manager, 1 Business Analyst, 1 QA Engineer, and 2 BI Engineers.</p> <h3>Project Tech Stack </h3> <p>Main Tech Stack: Databricks (Spark, Delta Lake, SQL Warehouses), Azure Synapse, Azure SQL, Power BI (DAX, semantic modeling, RLS), SQL.</p> <h3>What You’ll Do</h3> <ul> <li>Design and implement scalable data pipelines and lakehouse architectures using <strong>D</strong>atabricks (Delta Lake, Spark)</li> <li>Execute migration from Azure Synapse to Databricks, ensuring performance, and reliability improvements</li> <li>Develop and optimize Databricks Data Warehouse for analytics and BI workloads</li> <li>Build and maintain semantic models to support enterprise reporting and self-service analytics</li> <li>Partner with analytics and business teams to deliver high-quality Power BI datasets and dashboards</li> <li>Write, optimize, and tune complex SQL queries for large-scale analytical workloads</li> <li>Ensure data quality, reliability, and governance across the analytics platform</li> <li>Contribute to architecture decisions, best practices, and standards for data engineering</li> </ul> <h3>What You Bring</h3> <ul> <li>5+ years of experience in data engineering or analytics engineering roles</li> <li>Strong hands-on experience with Databricks (Spark, SQL)</li> <li>Advanced SQL skills, including performance tuning and query optimization</li> <li>Experience migrating data platforms, ideally Azure Synapse → Databricks</li> <li>Experience with Power BI, including dataset modeling</li> <li>Strong understanding of Kimball Data Warehousing approach, star schemas, and analytics best practices</li> <li>Experience working with cloud data platforms</li> </ul> <h3>English level