Senior Data Engineer
Chicago, IL (Hybrid, 3 days onsite) • Salary: $150,000 to $200,000 + Bonus
About the role
This is a rare opportunity to join a major enterprise at the beginning of its cloud data transformation, helping shape a modern Azure Databricks platform that will power analytics, data products, and future AI initiatives. You'll have genuine ownership, influence technical direction, and help define engineering standards from day one.
The Company
They are a globally recognised organisation investing heavily in the future of Data & AI. With a growing Data Engineering function and strong executive backing, they are building a centralised data platform designed to support analytics, operational reporting, and advanced machine learning use cases. This is a high-impact environment where engineers are trusted to solve complex challenges, drive best practice, and contribute to long-term platform strategy.
Responsibilities
- Play a key role in building and scaling a modern Azure Databricks ecosystem
- Design and develop end-to-end data pipelines from ingestion through to consumption
- Build scalable ETL/ELT, streaming, and CDC solutions
- Develop with Python, SQL, PySpark, Spark, and Azure Databricks
- Implement Delta Lake and Lakehouse architecture patterns
- Migrate and modernise legacy warehouse environments
- Optimise data models, schemas, and platform performance
- Establish CI/CD, automated testing, monitoring, and engineering best practice
- Troubleshoot complex production issues and improve platform reliability
- Contribute to code reviews and support knowledge sharing across the team
- Partner closely with analytics, platform, and business stakeholders
Requirements
- Strong commercial experience in Data Engineering
- Deep expertise with Azure Databricks, Spark, and PySpark
- Advanced Python and SQL development skills
- Proven experience building and owning production-grade data pipelines
- Strong understanding of ETL/ELT, data modelling, and Lakehouse architectures
- Experience with orchestration, CI/CD, testing, and monitoring
- Ability to explain technical decisions, trade-offs, and optimisation strategies
- Comfortable working in evolving, greenfield environments
- Experience within large-scale enterprise environments is advantageous
Benefits
- Significant influence over a rapidly growing data platform
- Exposure to large-scale cloud and AI transformation programmes
- Modern Azure and Databricks technology stack
- Clear progression opportunities as the Data Engineering function expands
- Collaborative, high-performing engineering culture