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Engineering Data Analyst Jobs in Detroit, MI (NOW HIRING)

Epoch Biodesign

Senior Performance Analyst

Wixom, MI · On-site

$118K - $145K/yr

Working closely with controls, design, and systems engineers, you will transform operational and process data into scalable, automated analytics that enable commissioning, fleet monitoring, investor ...

vaaridatech

Warranty Analysis Engineer

Auburn Hills, MI · Hybrid

Proficiency in Microsoft Office tools and engineering data analysis platforms . Optional skills: * Experience working with OEMs or Tier-1 automotive suppliers. * Familiarity with vehicle diagnostics ...

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All JobsEngineering Data Analyst JobsEngineering Data Analyst Jobs in Detroit, MI

Engineering Data Analyst information

See Detroit, MI salary details

$33.7K

$81.8K

$134.6K

How much do engineering data analyst jobs pay per year?

As of Sep 12, 2026, the average yearly pay for engineering data analyst in Detroit, MI is $81,811.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,900.00 and $96,000.00 per year, depending on experience, location, and employer.

What is an engineering data analyst?

An Engineering Data Analyst is a professional who uses data analysis techniques to support engineering projects and decision-making. They collect, clean, and interpret large sets of engineering data, often using specialized software tools. Their work helps identify trends, optimize processes, and improve the efficiency and quality of engineering solutions. They often collaborate with engineers and project managers to turn data insights into actionable recommendations.

What are the key skills and qualifications needed to thrive as an engineering data analyst?

To thrive as an Engineering Data Analyst, you need strong analytical skills, proficiency in mathematics and statistics, and a background in engineering or a related quantitative field. Familiarity with data analysis tools such as Python, R, SQL, and visualization platforms like Tableau or Power BI, along with relevant certifications, is often required. Attention to detail, problem-solving ability, and effective communication help you interpret data and translate findings for technical and non-technical stakeholders. These skills are crucial for transforming complex engineering data into actionable insights that drive process improvements and innovation.

What are some common challenges faced by engineering data analysts when working with cross-functional teams?

Engineering Data Analysts often collaborate with teams such as software engineers, project managers, and product designers. A common challenge is bridging the gap between complex analytical findings and actionable insights for non-technical colleagues. Clear communication and the ability to translate data into practical recommendations are essential. Additionally, managing multiple priorities and ensuring data integrity across various sources can be demanding but is crucial for successful project outcomes.
Engineering Data Analyst jobs near you
Infographic showing various Engineering Data Analyst job openings in Detroit, MI as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $81,811 per year, or $39.3 per hour.

Healthcare SAS Programmer/Data Analyst

Southfield, MI • On-site

Palnar
IT Services • 201 - 500 employees
Learn more about Palnarexternal

Full-time

Re-posted 22 days ago

Job description

Top 3 Required Skills/Experience:
Minimum of five years of SAS and SQL programming to create reports and dashboards.
Working with large data sources and analyzing pharmacy data
Analytical experience in the pharmacy services division and with PBM
Required Skills/Experience:
Ability to design and develop SharePoint site and use Dundas charts/excel web services, Access, and SAS data sources.
Knowledge of PBM systems and tools.
Excellent analytical, planning, problem solving, verbal, and written skills to communicate complex ideas.
Excellent knowledge and use of existing software packages (PowerPoint, Excel, Word, etc.).
Strong working knowledge of data languages such as SAS or SQL.
Ability to work independently, within a team environment, and communicate effectively with employees at all levels.

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