Business Intelligence Data Modeler Engineer II

Class Valuation, LLC
Chicago, IL, United States
16 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Compensation
$116,000.0 - $144,000.0
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Agile Methodology Data Analysis Business Systems C Sharp (Programming Language) Data Validation Information Engineering Data Governance Extract Transform Load (ETL) Data Security Data Structures Data Warehousing
+23 more
Relational Databases Dimensional Modeling Python (Programming Language) Microsoft SQL Server Performance Tuning Power BI SQL Databases Data Streaming Transact-SQL Qliksense Scripting Azure Data Factory Database Performance Microsoft Fabric Data Lakes Pyspark Information Technology Data Analytics Physical Data Models Azure Synapse Analytics Data Pipelines Databricks Programming Languages

Job description

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.

Requirements

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, OneLake or Microsoft Fabric. Analytics & BI Tools: Familiarity with Business Intelligence (BI) platforms such as Microsoft Power BI and Qlik Sense, and experience supporting enterprise reporting. Programming & Scripting: Exposure to Python, PySpark, Databricks, or programming languages like Java or C# is a plus. Data Governance & Security: Understanding of data governance principles, access controls, and data protection best practices. Business Acumen: Experience working with operational analytics domains such as Human Resources (HR), Finance, or Risk Management; professional services industry experience is a plus. Collaboration & Communication: Strong problem-solving, interpersonal, and communication skills with the ability to work cross-functionally. Work Style: Highly organized, self-motivated, and able to thrive in a fast-paced, Agile project environment managing multiple priorities.

If you’re ready to help shape how data drives smarter decisions and deliver impactful insights as a Business Intelligence Data Modeler Engineer II, we’d love to hear from you!

Benefits & conditions

The base salary range below represents the low and high end of the salary range for this position in Chicago. This range may differ based on your geographic location and cost of living considerations. At Kirkland & Ellis, we consider compensation more than just a base salary. We offer an exceptional range of flexible benefits including comprehensive healthcare, paid time off, and retirement. We also offer personal support and tailored learning and development opportunities all designed to help you realize your full potential both in life and at work.

Compensation Range:

Chicago: $116,000 - $144,000

About the company

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.

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