Analytics Engineer, Service Parts
Rivian · Plymouth, MI, US
Apply directly on Rivian’s careers site — no account needed.
About the role
The Analytics Engineer, Global Distribution Strategy (GDS) for Service Parts, supports the governance and standardization of Service Parts Master Data and other essential service parts data. This individual will help monitor data quality against defined targets and thresholds, and assist in maintaining the Service Parts Quality Index — a consolidated scorecard measuring data integrity across key dimensions such as Accuracy, Completeness, Timeliness, and Freshness. Working under the guidance of senior team members, this role will execute data quality checks, build reports and dashboards, and support broader GDS analytics needs, helping ensure service parts data is reliable and ready for analytical use across the organization.
Data Quality Monitoring: Run and maintain data quality checks that feed the Service Parts Quality Index. Track data integrity across key dimensions — Accuracy, Completeness, Timeliness, and Freshness — and flag issues to the team.- Governance Support: Help set up governance standards for Service Parts Master Data, including assisting in defining data quality rules, targets, and thresholds, and maintaining the supporting documentation.
- Issue Investigation: Investigate data quality issues, identify root causes where possible, and escalate findings with supporting analysis to senior team members for process or system follow-up.
- Analytics Support: Assist in building and maintaining data models and datasets used by the GDS team, following established patterns and best practices.
- Reporting: Build and maintain scorecards, dashboards, and recurring reports that communicate data quality status and trends to the Service Parts team.
- Collaboration: Work with team members and partner functions to gather requirements, validate data, and support consistent data definitions across the service parts organization.
Education: Bachelor's degree in Data Science, Business Analytics, Supply Chain Management, Engineering, or a related field.- Technical Skills: Working proficiency in SQL; familiarity with data transformation tools (e.g., dbt, databricks, amazon redshift) is a plus. Foundational knowledge of Python or Java is also a plus. Interest in or exposure to applying analytics and ML techniques to operational problems.
- Data Quality Awareness: Understanding of data quality concepts such as accuracy, completeness, and timeliness; experience with master data is a plus.
- Domain Knowledge: 1–3 years of experience in analytics, supply chain, distribution, or a related data-focused role. Exposure to SAP or similar ERP data is a plus.
- Analytical Skills: Ability to work with datasets, build reports and dashboards. Knowledge of Agentic AI & LLM tooling: Claude, Gemini, ChatGPT — workflow automation, MCP integrations, prompt engine.
- Communication: Clear written and verbal communication, with the ability to explain data issues and findings to teammates and stakeholders.
- Mindset: Detail-oriented, eager to learn, and comfortable working in a structured team environment with guidance from senior colleagues.
Description sourced from the public Indeed listing — this role isn't indexed from the company's career page yet.
Skills
- SQL
- Python
- Java
- dbt
- Databricks
Never be applicant #200 again
Every job here is indexed straight from company career pages — often hours after it opens, before it reaches the big boards. Create a free account and get your best matches in a twice-daily digest.
- Your best matches, twice a day
- No duplicates, no ghost jobs, no recruiter spam
- Every job free to browse — pay only when you apply
Get my matched jobs
Free account — no card required
93 119 live jobs · 17 642 companies tracked · 173 added today