Business Intelligence Data Modeler Engineer
What You'll Do
If you're someone who gets excited about building the data structures that make analytics actually work, this role is worth a close look.
As a Business Intelligence Data Modeler Engineer II, you'll be at the center of how data gets organized, accessed, and put to use across the enterprise. You'll work directly with business analysts, data engineers, and stakeholders to design data models that fuel reporting and analytics, while helping shape the broader data strategy. It's a role that calls for both technical depth and genuine curiosity about how a business operates.
Day to day, you can expect to:
- Work on conceptual, logical, and physical data models that underpin enterprise reporting and analytics.
- Partner with stakeholders to translate business requirements into well-structured, scalable data solutions.
- Contribute to the design of ETL processes that move data efficiently into BI platforms and warehouses.
- Build and enforce data quality checks to keep information accurate, consistent, and trustworthy.
- Monitor and tune data models and database performance so queries run efficiently.
- Create and maintain solid documentation of models, schemas, and data flows, in alignment with governance standards.
- Support access control and data security design for sensitive datasets.
- Write sophisticated SQL queries for ad hoc analysis, validation, and troubleshooting.
- Participate as a data subject matter expert across Agile sprints, from analysis through UAT.
- Develop deep familiarity with business domains and systems to better support strategic work.
- Keep pace with evolving tools, technologies, and best practices in data modeling and analytics.
What You'll Bring
A bachelor's degree in computer science, a related field, or equivalent hands-on experience, plus at least seven years working in data modeling, data warehousing, and ETL.
Required skills and experience:
- Strong working knowledge of dimensional modeling, including fact tables, star and snowflake schemas, slowly changing dimensions, and tools like Erwin.
- Solid command of SQL (including T-SQL) and deep experience with relational databases, particularly Microsoft SQL Server.
- Practical experience building data pipelines using ETL or ELT approaches and tools like Azure Data Factory, with exposure to platforms such as Azure Synapse Analytics, OneLake, or Microsoft Fabric.
- Familiarity with BI tools like Power BI and Qlik Sense, and experience supporting enterprise-level reporting.
- Understanding of data governance principles, access controls, and data protection practices.
- Experience working with operational data domains such as HR, Finance, or Risk Management.
- Clear, confident communication skills and the ability to collaborate across technical and non-technical teams.
- An organized, self-directed work style that holds up under shifting priorities in a fast-moving environment.
Nice to have: Exposure to Python, PySpark, Databricks, Java, or C#. Professional services industry background is a plus.
Compensation
The base salary range for this position in Chicago is $116,000 to $144,000. Actual compensation may vary based on location and cost of living. In addition to base salary, this role includes a strong benefits package covering comprehensive healthcare, paid time off, retirement, and access to professional development and personal support resources.
