Senior Data Engineer (Databricks, SQL)

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.
From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.
What powers it all? Our people are ambitious, collaborative, and constantly evolving.
About the Client
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.
Project Team
Team composition: 4 Senior Data Engineers, 1 Project Manager, 1 Business Analyst, 1 QA Engineer, and 2 BI Engineers.
Project Duration
6-month engagement with the possibility of extension.
Main Tech Stack: Databricks (Spark, Delta Lake, SQL Warehouses), Azure Synapse, Azure SQL, Power BI (DAX, semantic modeling, RLS), SQL.
What You’ll Do
Design and implement scalable data pipelines and lakehouse architectures using Databricks (Delta Lake, Spark)
Execute migration from Azure Synapse to Databricks, ensuring performance, and reliability improvements
Develop and optimize Databricks Data Warehouse for analytics and BI workloads
Build and maintain semantic models to support enterprise reporting and self-service analytics
Partner with analytics and business teams to deliver high-quality Power BI datasets and dashboards
Write, optimize, and tune complex SQL queries for large-scale analytical workloads
Ensure data quality, reliability, and governance across the analytics platform
Contribute to architecture decisions, best practices, and standards for dat