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 support these goals, Leidos is hiring a Mid-level 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 in support 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.
Responsibilities:
Design, build, and maintain scalable data systems for large-scale data processing and storage.Collaborate with cross-functional teams to gather requirements 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.
Requirements Education & Skills:
Bachelor's degree in computer science, Information Technology, or related field4+ 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 experience with Hadoop ecosystem components (e.g., HDFS, Spark, Hive)Experience with data flow management and orchestration toolsExperience with implementing database technologiesUtilize containerization technologies such as Docker, Podman, Kubernetes, or similar.Strong problem-solving skills and ability to work in a fast-paced environment.
Preferred Skills:
PhD degree 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 experience 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 understanding of Database, Data Warehouse, Datalake, Lakehouse, and scenarios where each of them would be a preferred fit.
If you are a self-starter with a passion for data engineering and want to make a significant impact in a growing company, we want to hear from you!
Anticipated pay range for this role: $82,000 - $92,000 - $102,000
Original Posting Date:********
While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
Pay Range:Pay Range $65,000.00 - $117,500.00
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
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