Data-Driven Quality Engineer

Here at Scout Motors, we're carrying forward the heritage of one of the most iconic American vehicles in history. A vehicle dating back to 1960. One that forged the path for future generations of rugged SUVs and will do so once again.

But Scout is more than just a brand, it’s a legacy steeped in a culture of exploration, caretaking, and hard work.

The Scout brand is all about respect. Respect for the environment by developing electric vehicles with the capability to get you to any location. Respect for the past and the future by taking an iconic American brand that hasn’t been around for a while, electrifying it, digitizing it, and loading it with American innovation. Respect for communities by creating a company that stands for its people and its customers. And respect for both work and play, with vehicles that are equally at home at a camp site, a job site, or on a Tuesday commute.

At Scout Motors, we empower our talented, inclusive, and entrepreneurial teams to innovate. What makes a Scout employee? Someone who is a visionary and a leader, who seeks new paths and shares lessons learned. A knowledgeable doer who collaborates across the company to build better. A go-getter with unrivaled passion.

Join us at Scout Motors and be part of shaping the future of transportation. If you're ready to drive change and make history, apply now!

About the team

The Production Quality Department within Scout includes Body Shop, Paint Shop, General Assembly and Central Quality Management Teams.  A Data-Driven Quality Senior Specialist at Scout Motors plays a pivotal role within the Quality Department by ensuring that data-driven insights inform and enhance quality management processes. This position focuses on leveraging data analytics to uphold and improve the quality standards of Scout Motors.

What you’ll do

Become part of an iconic brand that is set to revolutionize the electric pick-up truck & rugged SUV marketplace by achieving the following:

• Ingest data from legacy and modern IT systems (e.g., JIRA, Confluence, on-prem/plant systems, SQL/NoSQL sources, flat files, APIs) into a Databricks lakehouse.
• Build robust ELT pipelines with Python, SQL, and PySpark; model data for analytics (Delta Lake, medallion architecture) and enforce governance with Unity Catalog.
• Implement automated data quality checks and reconciliation (e.g., Great Expectations/Deequ) and design lineage/observability for pipelines and jobs.
• Develop forecasting, anomaly detection, and root-cause analytics using Databricks ML, MLflow, and the Model Registry; operationalize models via batch jobs or inference endpoints.
• Create KPI calculations for manufacturing/quality (e.g., FPY, PPM, Cp/Cpk, SPC trends) and document them as a single source of truth.
• Visualize results in Sigma Computing and Power BI (including DAX measures), and deliver lightweight custom React web apps for interactive diagnostics.
• Orchestrate and productionize workloads with Databricks Workflows, implement CI/CD (Git/GitHub Actions/Azure DevOps), and write unit/integration tests (pytest).
• Cross-functional data & LLM alignment: Proactively coordinate with Production/Manufacturing (shopfloor, MES/MOM), Manufacturing IT, data owners/stewards, and the enterprise LLM/OpenAI platform team to ensure data availability, access, SLAs, and safe model functionality.

Location & Travel Expectations:

• This role will be based out of the Scout Motors location in Columbia, SC/ Blythewood, SC.
• The responsibilities of this role require daily attendance in office with in-person meetings and events regularly. 
• Applicants should expect that the role will require the ability to convene with Scout colleagues in person and travel to participate in events on behalf of the company from time to time.

What you’ll bring 

We expect all Scout employees to have integrity, curiosity, resourcefulness, and strive to exhibit a positive attitude, as well as a growth mindset. You’ll be comfortable with change and flexible in a fast-paced, high-growth environment. You’ll take a collaborative approach to achieve ambitious goals. Here's what else you'll bring: 

• Education/Certifications:
  • A Bachelor’s or Master’s in Computer Science, Data/Industrial/Mechanical Engineering, or related field.
  • Nice to have: Databricks Data Engineer Professional and/or Machine Learning Professional.
• Years of Experience required in type of role: 4+ years in data engineering/analytics or ML engineering, including 2+ years hands-on with Databricks/Spark.
• Communication:
  • Ability to translate complex data and model outputs into clear business decisions for technical and non-tech