Data Engineer

About Bridgeway

Bridgeway is a rapidly growing Pittsburgh based company that is already among the country’s largest specialty transportation providers. Join an exciting and dynamic work environment where Team Members work together to deliver world class support to our customers, drivers, agents and carriers. With over a half a million loads annually, and a legacy of service to customers in critical industries, Bridgeway has a history of solving the country’s toughest transportation problems. Join our Team and become the Future of Freight!

About the Position

As a key member of the IT Transformation team, you will help build and scale the data foundation that powers our logistics operations and AI initiatives. This role is responsible for designing reliable data pipelines, integrating data from multiple operational systems (TMS, CRM, carrier platforms, market data), and delivering clean, trusted datasets for analytics, automation, and AI initiatives

What You’ll Do:

• Build and maintain ETL/ELT pipelines from TMS, CRM, EDI, and third-party freight data sources
• Develop and optimize cloud-based data architecture
• Create reliable data models for pricing, margin, operational reporting, and AI use cases
• Improve data quality, automation, and performance
• Build curated data layers for Power BI and other reporting tools; creating reusable data models and views
• Partner with analysts and business teams to define data requirements
• Support forecasting and pricing models
• Prepare and structure data for machine learning and AI initiatives

What We’re Looking For:

• 5+ years of data engineering experience
• Strong SQL and Python skills
• Experience with cloud platforms (AWS, Azure, or GCP)
• Hands-on experience with tools like Airflow, dbt, or Fivetran
• Strong problem-solving and troubleshooting skills
• Bonus: Experience in logistics, freight brokerage, or supply chain

What Success Looks Like

• Reliable pipelines with minimal downtime or manual intervention
• Clean, trusted operational data available in near real time
• Faster reporting and decision cycles for operations and pricing
• Reduced manual data work across teams
• A scalable data foundation ready for automation and AI