United States onlyPosition Description Redhorse Corporation (Redhorse) is seeking an exceptional Data Engineer to build and maintain the ETL pipeline supporting the development of predictive maintenance technology for the United States Marine Corps ground vehicles. You will serve on a remote cross-functional engineering team and contribute to establishing and continuously improving an AI/ML analytics platform that aims to increase vehicle availability while reducing the life cycle maintenance costs. Leveraging many maintenance-related data sources, you will facilitate the development of AI/ML models that will forecast system and part failures for USMC fleet vehicles. At Redhorse Corporation, our mission is to transform the way the government interacts with and utilizes data and technology to better serve its citizens. Our approach combines design thinking, Lean Startup, and Agile principles, driven by our world-class data scientists and engineers. We are hiring a creative, motivated, and talented Data Engineer for the Condition Based Maintenance (CBM+) Program to serve as a data custodian, responsible for provenance, accuracy, storage, and availability throughout project execution, building and maintaining ETL pipelines to support a high-priority preventative maintenance project for the US Marine Corps.
Essential Functions:
- Develop, maintain, and automate ETL processes that ingest data from various sources.
- Automate the monitoring of data pipelines to ensure the integrity and quality of the data for AI/ML models and BI tools.
- Champion MLOps and DevOps principles to streamline deployment, monitoring, and maintenance of data applications and machine learning models.
- Work under general guidance, demonstrate an initiative to develop approaches to solutions independently, review architecture, and identify areas for automation, optimization, right-sizing, and cost reduction to support the overall health of the environment.
- Utilize version control for tracking changes to code, data, and model artifacts, enabling seamless collaboration and reproducibility.
- Engage with data scientists, software developers, BI developers, users, and stakeholders to understand data requirements and gather feedback.
- Document work in diagrams and written reports.
- Mentor and develop junior data engineers and team members.
Minimum Basic Requirements for Skills, Experience, Education and Credentials include:
- US citizen with a Secret US government clearance. Applicants who are not US Citizens, and those who do not have a current and active Secret security clearance will not be considered for this role.
- Bachelor’s degree in Computer Science, Data Science, or a related field or equivalent professional or military experience.
- 4+ years of professional data engineering with experience managing database solutions, automating workflows, and supporting AI/ML model development.
- Experience with Python.
- Experience with Agile software development methodologies and tools such as Jira, Confluence, GitHub, and/or GitLab.
- Well versed in modern software architectures like micro-services as well as front-end frameworks.
- Experience designing and delivering software solutions in AWS cloud environments.
- Familiarity with automation tools and practices to enhance workflow efficiency.
- Familiarity with CI/CD software development practices.
- Demonstratable expertise in building and maintaining data pipelines for AI/ML platforms.
- Experience designing database schemas for optimal performance and minimal cost.
- Ability to synthesize requirements underlying feature requests, recommend alternative technical and business approaches, and facilitate engineering efforts to meet aggressive timelines.
- Experience writing and speaking about technical concepts to business, technical, and lay audiences and give presentations.
Preferred Qualifications include:
- Advanced degree in Computer Science, Data Science, or related field or equivalent professional or military experience.
- Proficiency in implementing model monitoring and observability processes to ensure model performance and reliability in production.
- Experience with MLOps practices, including model versioning, containerization, orchestration, and continuous integration/continuous deployment (CI/CD) pipelines.
- Experience delivering software or technical solutions to the DoD/Intelligence Community is preferred.
- Familiarity with MLflow managing end-to-end machine learning workflows.
- Experience in Digital Signal Processing (DSP) and CAN bus J1939 data.
- Experience with the Advana Platform.
- Experience working with SQL, Spark, and/or PySpark.
- Experience with Databricks
- Experience with preparing data for BI tools like Qlik.
- Experience with data from JLTV, MVTR, and LVSR platforms.
