Senior Data Engineer

Location: Chicago, IL (Hybrid, 3+ Days Onsite) Pay: $150K-$190K Base + Bonus About the Role A leading global professional services organization is undertaking a major enterprise-wide Data & AI modernization initiative and is investing heavily in a centralized cloud-based data ecosystem. This team is building the foundation for analytics, business intelligence, operational reporting, and future AI-driven capabilities. This is an opportunity to join early in the journey and play a key role in shaping a modern Azure Databricks environment, building production-grade data pipelines, and helping establish engineering standards within a growing data organization. Responsibilities Design and build end-to-end data pipelines from ingestion through transformation and downstream consumption. Develop scalable ETL/ELT solutions supporting both batch and streaming/CDC workloads. Build solutions using Python, SQL, PySpark, Spark, and Azure Databricks. Implement Lakehouse architectures and Bronze/Silver/Gold data models. Migrate and modernize legacy warehouse environments into a centralized cloud platform. Optimize data models, schemas, performance, and scalability. Establish CI/CD, automated testing, monitoring, alerting, and operational best practices. Troubleshoot complex production data issues and support platform reliability. Participate in code reviews and mentor junior-level engineers. Must-Have Qualifications 6+ years of hands-on Data Engineering experience. Strong Azure Databricks and Spark/PySpark expertise in production environments. Advanced Python and SQL development skills. Experience owning end-to-end data pipelines from source through consumption. Strong ETL/ELT, data modeling, and Lakehouse architecture experience. Experience with CI/CD, testing, monitoring, orchestration, and production support. #J-18808-Ljbffr