Business Intelligence Data Modeler Engineer II Job Chicago area,Illinois USA,IT/Tech

About Kirkland & Ellis

At Kirkland & Ellis, we don’t just meet the standard for legal excellence — we set it. Our culture is built on teamwork, ingenuity and an unwavering commitment to continuous growth. We tackle the most sophisticated legal challenges with bold ideas and innovative solutions, powered by the exceptional experience and ambition of our 7,000+ people, including 4,000+ attorneys, across 24 offices worldwide.

Our dedicated professionals share our lawyers’ commitment to excellence and show up each day to do meaningful work that helps drive global business, investment and innovation forward.

About Kirkland & Ellis

What You’ll Do

Are you passionate about turning complex data into meaningful insights that drive business decisions?

As a Business Intelligence Data Modeler Engineer II, you’ll play a critical role in shaping how data is structured, accessed, and for enterprise business intelligence. Partnering closely with business analysts, data engineers, and business stakeholders, you’ll design and support development of data models that power reporting, analytics. This role blends technical expertise with business insight, giving you the opportunity to influence how data supports enterprise-wide decision-making.

Data Modeling Design:
Create and maintain conceptual, logical, and physical data models that support reporting and analytics across enterprise systems.
Business Partnership:
Collaborate with stakeholders to translate business needs into scalable data structures and solutions.
ETL Development Support:
Contribute to the design of Extract, Transform, Load (ETL) processes to ensure efficient data movement into Business Intelligence (BI) platforms and warehouses.
Data Quality & Validation:
Implement checks and rules to ensure data accuracy, consistency, and reliability across systems.
Performance Optimization:
Continuously monitor and refine data models and database performance for efficient querying and reporting.
Documentation & Governance:
Maintain clear documentation of models, schemas, and data flows while adhering to data governance standards.
Data Security:
Help design access controls and security measures to protect sensitive data.
Advanced Querying:
Develop and utilize Structured Query Language (SQL) queries for ad hoc analysis, troubleshooting, and data validation.
Agile

Collaboration:

Participate in Agile workflows across analysis, development, quality assurance (QA), and user acceptance testing (UAT) phases as a data subject matter expert.
Domain Expertise:
Build strong knowledge of business systems and data domains to support strategic initiatives.
Continuous Learning:
Stay current with evolving technologies and industry trends in data modeling and analytics.

What You’ll Bring

Education:

Bachelor’s degree in computer science, a related field, or equivalent practical experience.
Experience:

7+ years of experience in data modeling, data warehousing, and ETL processes.

Required

Data Modeling Expertise:
Strong Hands-on experience of dimensional modeling, fact tables, star/snowflake schemas, slowly changing dimensions (SCDs), and tools like Erwin.
Technical

Skills:

Expertise with SQL (including Transact-SQL) and deep experience with relational database systems such as Microsoft SQL Server.
Data Engineering Knowledge:
Experience with data pipelines using ETL or Extract, Load, Transform (ELT) techniques and tools such as Azure Data Factory (ADF) to load data into analytics data marts, data warehouses and data lakes. Experience with analytics data platforms such as Azure Synapse Analytics, One Lake or Microsoft Fabric.
Analyti…