Data Engineer - Microsoft BI Focus

Roadrunner Transportation Services•Downers Grove, IL

6h•$70,000 - $110,000•Hybrid

About The Position

We are seeking an experienced Data Engineer with expertise in the Microsoft Business Intelligence stack to design, build, and maintain robust data pipelines and analytical models. This role focuses on backend data engineering using strong SQL skills, SQL Server Analysis Services (SSAS) for tabular modeling, and Power BI for data visualization and reporting. The ideal candidate will support data-driven decision-making by ensuring high-quality, scalable data solutions. Experience in the transportation and logistics industry is preferred, as the role involves working with datasets related to supply chain, routing, inventory, freight, and operational efficiency. Roadrunner Freight is building something special with great people, a winning culture and a differentiated service offering in the marketplace. Join us today to grow your career! Roadrunner’s Smart Long Haul is revolutionizing the industry with significant investments in technology, a culture of continuous improvement, and intelligent and efficient direct routing. A Top 100 Trucking company by Inbound Logistics and a Top Tier Service Carrier by Mastio, Roadrunner is an LTL industry leader on the rise. As a long-haul, metro-to-metro LTL carrier, Roadrunner offers more direct routes than any other nationwide Less-than-Truckload carrier in the United States. With a nationwide presence, terminals across 40+ markets, and more than $400 million in revenue, the company’s Smart Long-Haul Network is the preferred choice for shippers looking to move freight quickly and reliably. Roadrunner is growing and looking for a highly motivated Data Engineer - Microsoft BI Focus to join our winning team. If you are results driven and looking for a rapidly growing company with high growth and earnings potential, apply today! We Run Safe. We Run Smart. We Run Together.

Requirements

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent experience).
5+ years of experience as a Data Engineer, BI Developer, or similar role with hands-on Microsoft BI stack.
Strong SQL proficiency: Expert in writing advanced T-SQL queries, performance tuning, indexing, and handling large datasets.
Expertise in SQL Server Analysis Services (SSAS) Tabular models: Building semantic models, DAX/MDX, KPIs, perspectives, and processing.
Proficiency in Power BI: Data modeling, Power Query, DAX for calculations, report/dashboard development, and publishing/sharing.
Experience with SSIS for ETL pipelines and data integration.
Familiarity with data warehousing concepts (e.g., star/snowflake schemas, dimensional modeling).
Knowledge of Azure data services (e.g., Azure SQL, Azure Analysis Services, Fabric) is a plus.
Strong problem-solving, analytical, and communication skills.
Ability to work independently and in cross-functional teams.

Nice To Haves

Experience in the transportation, logistics, or supply chain industry (e.g., working with data on fleet management, routing optimization, inventory tracking, or freight analytics).
Familiarity with SSRS for reporting or other BI tools.
Certifications: Microsoft Certified: Data Analyst Associate, Power BI Data Analyst, or Azure Data Engineer.
Experience with Python or other scripting for data manipulation is a bonus.

Responsibilities

Design, develop, and optimize ETL/ELT processes using SQL Server Integration Services (SSIS) or similar tools to ingest, transform, and load data from various sources into data warehouses or lakes.
Build and maintain SSAS tabular models, including data modeling, DAX calculations, relationships, partitions, and row-level security.
Develop complex SQL queries, stored procedures, views, and functions for data extraction, aggregation, and performance tuning on SQL Server databases.
Create and support Power BI datasets, reports, and dashboards, connecting to SSAS models or direct data sources for interactive visualizations.
Collaborate with stakeholders to gather requirements, design data models, and ensure solutions meet business needs for reporting and analytics.
Implement data quality checks, governance, and monitoring to maintain accuracy and reliability of data pipelines.
Optimize data models and queries for performance, scalability, and cost efficiency.
Support migration or integration of legacy systems into modern Microsoft BI environments.