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United States
Remote only
Not Available
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Transportation Systems Data Engineer based in the United States.
Join an innovative engineering team developing advanced, data-driven solutions to improve transportation systems, road safety, and mobility. As a Transportation Systems Data Engineer, you will collaborate with transportation engineers, data scientists, software developers, and systems specialists to transform complex mobility data into actionable insights. You will design scalable data pipelines, build cloud-based analytics solutions, and apply machine learning and artificial intelligence to real-world transportation challenges. Your work will support traffic operations, incident management, safety monitoring, and intelligent transportation systems. This role offers the opportunity to work with large-scale datasets, emerging technologies, and multidisciplinary teams on projects that enhance infrastructure performance and community safety. If you enjoy solving complex technical problems and translating data into meaningful outcomes, this position offers an exciting opportunity to make a measurable impact.
Transportation Data Engineering and Analytics: Process, analyze, and integrate large-scale transportation datasets, including connected vehicle, telematics, traffic sensor, weather, crash, work zone, camera, and vehicle trajectory data. Develop analytical solutions that support traffic operations, transportation safety, incident management, and system performance monitoring.
Data Pipeline Development: Design, build, test, and maintain reliable batch and streaming data pipelines that support analytics, machine learning, visualization, and operational applications. Integrate information from multiple sources into unified transportation data platforms.
Cloud Architecture and Data Processing: Develop scalable cloud-based data architectures and workflows using platforms such as AWS, Google Cloud Platform (GCP), Oracle Cloud, Databricks, and Amazon S3. Optimize data processing, storage, and integration workflows to support large and complex analytical workloads.
Machine Learning and Artificial Intelligence: Develop, train, test, and evaluate machine learning, computer vision, and AI models for transportation applications, including lane closure detection, traffic-scene analysis, safety monitoring, and automated video analytics. Explore emerging techniques such as object detection, large language models, and vision-language models.
Data Visualization and Decision Support: Create interactive dashboards, visualizations, and analytical applications using tools such as Tableau, Power BI, R Shiny, or similar technologies. Translate complex analytical findings into clear insights, technical reports, and recommendations for transportation agencies and system operators.
Cross-Functional Collaboration: Work closely with transportation engineers, data scientists, software developers, researchers, agency stakeholders, and technology specialists throughout solution design, development, testing, and implementation. Ensure that technical solutions address operational requirements and real-world transportation challenges.
Research and Technical Documentation: Contribute to technical reports, research papers, presentations, project proposals, and supporting documentation. Communicate methodologies, analytical results, and project outcomes to technical and nontechnical audiences.
Agile Development and Continuous Improvement: Participate in Agile and Scrum workflows, including requirements definition, sprint planning, peer reviews, testing, and technical demonstrations. Apply collaborative software development practices and continuously improve analytical tools, data workflows, and solution quality.
Education and Experience: Bachelor's degree in Engineering or a related field, along with at least five years of relevant professional experience.
Transportation Data Expertise: Experience analyzing transportation, connected vehicle, traffic operations, safety, telematics, mobility, or other large-scale datasets. Familiarity with transportation engineering, intelligent transportation systems, traffic safety, and connected vehicle applications is highly desirable.
Programming and Data Engineering: Strong experience developing data pipelines and working with data processing, transformation, and storage technologies. Proficiency in Python and SQL, with experience in R or related data science tools, is an advantage.
Cloud Technologies: Experience with cloud-based data platforms and architectures. Familiarity with AWS services such as S3, Glue, and Athena, or equivalent services within GCP, Oracle Cloud, or other cloud environments, is preferred.
Big Data Processing: Knowledge of large-scale data processing technologies, including Polars, SQL, distributed computing, or comparable tools for managing complex datasets.
Machine Learning and Computer Vision: Experience developing and evaluating machine learning models using classification, object detection, computer vision, or large language model techniques. Exposure to video-processing pipelines, traffic-scene analysis, visual question answering, or vision-language models is an advantage.
Data Visualization: Experience building dashboards, interactive visualizations, or analytical applications using Tableau, Power BI, R Shiny, or similar platforms.
Data Integration: Ability to integrate and analyze information from multiple sources, including traffic sensors, vehicle systems, weather services, crash records, work zones, and camera data.
Software Development Practices: Familiarity with GitHub, version control, Agile, Scrum, peer reviews, testing, and collaborative development workflows.
Analytical and Problem-Solving Skills: Ability to investigate complex transportation challenges independently, develop practical technical solutions, and turn analytical results into actionable recommendations.
Communication and Collaboration: Strong written and verbal communication skills, with the ability to explain technical concepts and findings clearly to multidisciplinary teams, transportation agencies, and nontechnical stakeholders.
Professional Engagement: Demonstrated participation in or leadership within transportation research, technical organizations, professional associations, or industry conferences.
Security Requirements: No security clearance is required for this position.
Competitive Salary: Annual base salary ranging from $74,800 to $130,900, depending on qualifications, experience, and other relevant factors.
Remote Work: Fully remote position available to candidates located anywhere in the United States.
Healthcare Coverage: Medical, dental, and vision insurance.
Retirement Benefits: Access to a 401(k) retirement savings plan.
Employee Stock Ownership: Participation in an Employee Stock Ownership Plan (ESOP).
Paid Time Off: Paid leave and holidays to support work-life balance and personal commitments.
Life Insurance: Life insurance coverage as part of the employee benefits package.
Flexible Scheduling: Flexible work schedules designed to accommodate different working styles and personal needs.
Career Development: Opportunities to expand technical expertise, work with emerging data and AI technologies, and contribute to innovative transportation infrastructure projects.
Meaningful Work: The opportunity to improve transportation safety, mobility, infrastructure performance, and community resilience through advanced engineering and data analytics.
Collaborative Environment: Work alongside multidisciplinary experts on challenging projects involving transportation engineering, cloud technologies, machine learning, and intelligent transportation systems.
Security Clearance: No security clearance is required.