Test Data Operations Engineer

We are looking for a high-energy technically-mindedTest Data Operations Engineer to bridge the gap between physical benchmarking and digital this role you wont just be watching tests; you will influence how test data is captured refined and visualized. You will work directly with engineering teams to conduct automotive benchmarking then leverage modern toolsincluding SQL and Agentic AIto turn raw sensor data into actionable narratives for our cross-functional leadership.

This is an ideal role for a recent engineering graduate with a passion for data science and a hands-on hardware mindset.

Responsibilities

1. Test Execution & Refinement

• Support physical benchmarking and durability tests as needed ensuring instrumentation is correctly configured (familiarity withCANalyzer or similar tools is a plus).
• Collaborate with test teams to refine procedures ensuring that the data coming out of the lab is high-quality and analysis-ready.
• Act as the feedback loop between the lab and the database identifying gaps in current data collection methods.

2. Data Engineering & Visualization

• Own the end-to-end data pipeline: collect store and visualize test results usingSQLPythonHex and advanced dashboarding tools.
• ImplementAgentic AI workflows to automate routine data cleaning summarization and trend detection.
• Integrate 3rd party industry data to provide competitive context for our internal benchmarking results.

3. Cross-Functional Storytelling

• Translate complex engineering metrics into easy-to-digest data stories for Engineering and Manufacturing teams.
• Maintain a centralized data repository that ensures one version of the truth for all performance benchmarks.

Why This Role is Unique

Unlike traditional Test Engineer roles that end when the test is over or Data Analyst roles that never see the hardware this position gives youfull-stack visibility. You will help generate the data build the systems that house it and influence the tools that analyze it.

Qualifications

• Education: Bachelors degree in Mechanical Engineering Automotive Engineering Data Science or a related technical field.
• Data skills and background:
  • You believe that data is only useful if its understandable and accessible
  • Strong interpersonal skills to navigate a matrixed environment and the ability to explain technical concepts to non-engineers.
  • Foundational knowledge ofSQL for data extraction.
  • Exposure to or a deep interest inAgentic AI tools
  • Experience with (or ability to quickly learn) automotive communication tools likeCANalyzer.
• Curious mindset: You arent afraid to get your hands dirty in the lab to understand why a data point looks off.