Engineering Quality, Safety, and Compliance Intern

Inside the Role

Interns will gain knowledge and experience through exciting and real‑life learning opportunities. Interns must work in accordance with DTNA’s core values of passion, respect, integrity and discipline. Internship positions can be located at various DTNA locations across the US. We are looking for high performing and motivated individuals in various areas within DTNA organizations. DTNA internships begin each summer in May or June.

As an intern on the Engineering Quality (EQ) team, you’ll gain hands‑on experience improving how we manage and use data to support product quality. You’ll collaborate with EQ specialists, functional safety experts, design engineers, and cross‑functional teams to streamline processes and enhance the quality of our work products. Your work will focus on two key projects:

Help us optimize how quality‑related data (like DFMEAs, component specifications, and safety analyses) are created, stored, and shared. You’ll:

• Analyze end‑to‑end data creation and storage mechanisms for EQ work products.
• Identify redundancies and propose solutions to eliminate duplicates.
• Recommend automation and workflow improvements to replace manual processes.
• Ensure data storage and retrieval practices align with DTNA and industry best standards.
• Validate data and metadata quality to enable robust metrics across EQ and the broader engineering organization.
• (Bonus) Explore the interactions between EQ data and enterprise systems (Snowflake, Dataverse, SAP) and propose a unified data model to support future GenAI initiatives.

Impact:
Your work will help reduce inefficiencies, improve data models, and lay the foundation for advanced AI‑driven processes in Engineering Quality.

Work on projects that link design quality with insights from manufacturing and aftermarket data. You’ll:

• Identify what manufacturing plant and field data is most useful for DFMEAs.
• Map how this data can improve product design and service diagnostics.
• (Bonus) Develop data maps to support future AI‑driven DFMEA pilots and propose automated data delivery to expert teams.

Impact:
Your contributions will enable faster, more valuable DFMEA creation, reduce the cost of quality, and strengthen design decisions through real‑world data insights.

Interns in this role may have the opportunity to transition into a full‑time position subject to manager evaluations and business availability.

We provide a scheduled posting end date to assist our candidates with their application planning. While this date reflects our latest plans, it is subject to change, and postings may be extended or removed earlier than expected.

Salary placement is determined by your anticipated graduation year and ranges between $21 - $29 per hour.

• Professional development and networking events, including resume reviews/mock interviews
• Housing and transportation stipend
• Employee resource groups
• Event ticket offering (based on corporate availability)
• Company social events

• Analyze data workflows and identify opportunities for automation.
• Perform trend analysis on data quality and storage practices.
• Support projects that integrate design, manufacturing, and service data.
• Present findings and recommendations to senior management.
• Contribute to foundational work for future AI and data‑driven engineering processes.
• Lead and support efforts to foster an inclusive and welcoming workplace culture where everyone belongs

• Must be currently enrolled in a Bachelor’s program or higher from an accredited college/university OR have recently graduated within 1 year of the position start date (May/June)
• Strong oral and written communication skills
• Solid organizational skills
• Creative mindset
• Interpersonal skills and ability to work in a team environment

#LI-Hybrid

This position is open to applicants who can work in (or relocate to) the following location(s) - Portland, OR US. Relocation assistance is not available for this position.

Hybrid (4 days per week in office / 1 day remote). This schedule builds our #One…