Lucid is looking to design, build, and maintain robust data pipelines that power insights for validation and test operations in their powertrain dyno lab.
Requirements
- Direct experience with AVL PUMA Open, CONCERTO, or other AVL software platforms in a powertrain test or dyno environment
- Skilled in Python for ETL workflows, including libraries like Pandas and PyMDF
- Familiarity with AWS services (e.g., S3, Lambda, EC2) for data processing and storage
- Proficient in Docker and Git
- Experience with CI/CD pipelines is a plus
- Previous work with LabVIEW and SCADA systems is an asset
- Strong understanding of test lab data acquisition systems and sensor integration
- Knowledge of automotive protocols: CAN, Modbus, TCP/IP, and optionally, CCP/XCP or ASAP3
- Experience with relational databases like PostgreSQL or time-series DBs like InfluxDB
Responsibilities
- Develop and maintain data pipelines and interfaces specifically designed for AVL test systems
- Build, monitor, and optimize robust data pipelines to collect, transform, and store data from dyno labs and other validation systems
- Ensure accurate and high-fidelity data collection from AVL powertrain testbeds
- Create insightful dashboards and analytics using tools such as Tableau and Grafana
- Utilize Docker containers to manage microservices supporting test data ingestion and analytics
- Deploy in cloud environments (AWS preferred)
- Build connectors and interpreters for test data protocols including CAN, Modbus, TCP/IP, and AVL-specific data formats like MDF or ASAP3
Other
- Education: Bachelor’s degree in Electrical & Computer Engineering, Computer Science, or a related field
- Effective communicator, especially in cross-functional lab environments
- Detail-oriented with a proactive mindset and ability to manage competing priorities
