Operations Engineer Associate
Lockheed Martin
Camden, AR0–2 yrs3h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 2 years · Bachelor's degree
- Must know
- Data visualizationSQLPythonPower BITableauExcel
- Work
- On-site in Camden
- Pay
- Not stated by the employer.
- Skill demand
- Python40%SQL13%Data visualization7%of 99 similar entry-level jobs posted in the US this week
- Listed
- Oct 29, 2026 · still open
Sign in free to see which of these skills your resume already shows.
About the Role
Drives the producibility and quality of products and processes across engineering disciplines including industrial, manufacturing, process, test, and tool. Takes a data-driven approach, turning shop-floor and program data into actionable reports and insights for the site. You'll analyze industrial engineering data (cycle times, throughput, yield, scrap, labor, capacity) and translate it into metrics, dashboards, and recommendations that drive cost-effective decisions across Camden's manufacturing programs, partnering with program owners to embed insights into daily decisions and surface risks early.
Key Responsibilities
- Drive the producibility and quality of products and processes across engineering disciplines.
- Analyze industrial engineering data (cycle times, throughput, yield, scrap, labor, capacity).
- Translate data into metrics, dashboards, and recommendations.
- Partner with program owners to embed insights into daily decisions and surface risks early.
Requirements & Tech Stack
- SQL
- Python
- Power BI, Tableau, or Grafana
- Microsoft Office (Excel, Word, PowerPoint, Outlook)
- Excel tools: macros, PivotTables, VLOOKUP/XLOOKUP
Qualifications
- Bachelor's in Industrial Engineering, Industrial and Systems Engineering, Computer Science, or Data Analytics.
- 0 to 2 years of experience (including internships, co-ops, or academic projects) in manufacturing, data engineering, or process improvement.
- Proficiency in data analysis and visualization.
- Experience with R or other statistical languages.
- Familiarity building internal tools or automations that deliver analysis directly to end users, including AI/ML.
- Ability to translate technical results into clear business recommendations.
- Detail oriented, self-starter who thrives in a collaborative environment.
- Resilient, adaptable, and eager to learn in fast-paced environments.
- Interest in or exposure to the LM portfolio of products.
- Exposure to Lean Six Sigma principles.