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Staff Software Engineer - Infrastructure, Data Platform

Baton (A Ryder Technology Lab)
CompanyBaton (A Ryder Technology Lab)
CategoryEngineering
LocationSan Francisco
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted24 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
Who We Are Baton is Ryder ’s in-house product development group focused on harnessing emerging technologies to redefine transportation and logistics. With $10B in freight under management, our technology reaches every part of the U.S. economy. We design and ship category-defining software that enables Ryder and its 50,000+ customers—including some of the world’s most well-known brands—to plan and execute freight intelligently, efficiently, and cost-effectively. Our work includes everything from customer-facing software to the data platform that will power the next era of innovation at Ryder. Baton’s mission : enable supply chain on autopilot. Ryder acquired Baton in 2022 to power its next wave of digital products. We operate at startup speed, with Fortune 500 reach. If you have a passion for solving complex problems and creating impact for the engine of the American economy, you’ll love it here. Role:  Staff Software Engineer - Infrastructure Pod:  Data Platform Location:  Hayes Valley, San Francisco, CA Basic Job Details Job Type: Full Time Work Model: Hybrid Remote Days: Monday & Friday Office Days: Tuesday, Wednesday, Thursday Job Description As a Staff Software Engineer on our Data Platform team, you will lead the design, implementation, and continuous improvement of our foundational data systems, ensuring scalability, reliability, and efficiency. You'll architect data platforms, manage streaming pipelines, optimize cloud infrastructure, and champion best practices in infrastructure-as-code, observability, and system performance. The Data Platform's scope of impact is expanding faster than any one team can absorb, and this role exists to own that growth. You'll take end-to-end ownership of supply line visibility data integration, connecting the execution platforms operating across Ryder and Baton. Leveraging your expertise in distributed systems and real-time data processing, you'll mentor engineering teams, shape strategic technical direction, and give the organization a single view of its data across both the Baton and Ryder platforms. Responsibilities Design and Maintain Robust Data Architecture: Design, maintain, and optimize our data streaming and messaging architecture as the platform's scope continues to expand. Oversee Real-Time Data Streaming Platforms: Manage and enhance the real-time data streaming platforms, ensuring robust data ingestion and efficient processing. Own Cross-Platform Data Integration: Take end-to-end ownership of supply line visibility data integration, spanning third-party, in-house, and Ryder-managed execution platforms. Drive Major Integration Initiatives: Lead the architecture and delivery of large-scale integrations with enterprise supply chain execution systems. Simplify and Solve Data Challenges: Transform complex data challenges into streamlined, scalable, and maintainable technical solutions. Collaborative Stakeholder Engagement: Collaborate closely with both technical and non-technical stakeholders across Baton and Ryder to enhance data-driven decision-making and foster innovative data practices across the organization. Required Qualifications Data Integration Experience: Track record in solving real-time data challenges at large-scale enterprises, including common dual-write solutions Technical Leadership: Technical Leadership and cross-functional collaboration across an org Python Proficiency: Advanced proficiency coding in python at a Staff level Preferred Qualifications Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or a closely related technical field. Industry Experience: Demonstrated experience or a strong interest in the freight and logistics industry, with an understanding of its data-driven challenges and opportuni
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