Data Engineer

at  Leidos

Description
Are you interested in improving and shaping the transportation industry with a group of intelligent and motivated individuals? Consider joining the Leidos team operating the Federal Highway Administration (FHWA)’s Saxton Transportation Operations Laboratory (STOL), a USDOT research lab focused on the improvement of transportation operations, safety, mobility, and environmental impacts. STOL champions the integration of emerging technologies such as cooperative driving automation (CDA) and Vehicle-to-Everything (V2X) to revolutionize transportation.
Learn more about STOL here!
To enhance these goals, Leidos is hiring a Data Engineer to work in McLean, Virginia as part of a team of researchers developing the latest Connected and Automated Vehicle (CAV) technology. The position is a key part of the Leidos’ team supporting FHWA’s cutting-edge research. The work at STOL involves development and maintenance of various systems such as roadside data collection and storage, web mapping tools, communications and data transfer, simulation, and data analysis, as well as work on vehicle on-board software for automation and connectivity.
The Data Engineer will be part of a team of developers writing and extending a variety of applications and components aiding the future of transportation research, including connected vehicles and human factors. We are part of a larger FHWA research team in a relaxed, laboratory environment that pushes the boundaries of connected and autonomous vehicle technology for the FHWA. The team at STOL demonstrates capabilities associated with vehicle-to-vehicle and vehicle-to-infrastructure communication that will support the larger Intelligent Transportation System initiatives. We also study human factors, such as a driver’s ability to recognize and react to various situations, including interaction with automated vehicles. The ideal candidate will have a passion for big data and a strong technical background in designing, building, and maintaining scalable data systems.

REQUIREMENTS EDUCATION & SKILLS:

• Bachelor’s degree in computer science, Information Technology, or related field
• 4+ years of experience in designing and implementing data solutions.
• Ability to obtain Public Trust (which includes three years of immediate residency in the US).
• Strong experience with SQL and NoSQL databases (e.g., MySQL, MongoDB, InfluxDB)
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and automating cloud infrastructure deployments.
• Hands-on involvement with Hadoop ecosystem components (e.g., HDFS, Spark, Hive)
• Background working with data flow management and orchestration tools
• Prior exposure with implementing database technologies
• Utilize containerization technologies such as Docker, Podman, Kubernetes, or similar.
• Strong problem-solving skills and ability to work in a fast-paced environment.

PREFERRED SKILLS:

• Higher level education in Transportation Engineering, Systems Engineering, Computer Science, or other related fields.
• In-depth knowledge of Artificial Intelligence and Machine Learning tools in transportation.
• Hands-on involvement with BI tools such as Grafana, Tableau, and PowerBI.
• Experience with coding languages such as Python, Java, Spark, or similar.
• Ability to prioritize and manage a complex & changing data infrastructure.
• Good comprehension of Database, Data Warehouse, Datalake, Lakehouse, and scenarios where each of them would be a preferred fit.

• Design, build, and maintain scalable data systems for large-scale data processing and storage.
• Work with cross-functional teams to gather demands and drive data solutions.
• Execute innovative solutions involving the integration of ITS, CDA, C-V2X, and CAV applications to improve the transportation of people and goods through the implementation of cutting-edge algorithms as well as simulation approaches.
• Develop complex data flows and improve/maintain data pipelines for collecting, transforming, and loading data into data storage solutions.
• Work with sensor data, from automated vehicles and transportation infrastructure and apply Extract Load Transform (ELT) to make it AI/ML ready.
• Manipulate data and data flows for both existing and new systems including visualization.
• Analyze large-scale datasets to explain the performance of the transportation system and transportation technologies.
• Implement data quality and data governance processes.
• Monitor and optimize system performance, troubleshoot issues, and implement solutions.
• Research emerging technologies to determine impact on application execution.
• Provides input to staff involved in writing and updating technical documentation.
• Prepares reports on analyses, findings, and project progress.
• May serve as a technical team or task leader.