ZipRecruiter

Log In

1

Data Analytics Engineer Jobs in Dearborn, MI (NOW HIRING)

Premier Truck Rental

Senior Analytics Engineer

Detroit, MI · On-site

$103K - $142K/yr

Working closely with Data Engineering, Data Architecture, and the BI team, you will translate ... Mentor Analytics Engineer I / junior engineers, review their code, and set the modeling patterns ...

ArcelorMittal

Data Analytics Co-Op

Detroit, MI · On-site

Data Analytics Co-Op Location: Detroit, MI Who Are We? Are you ready to be part of a dynamic and ... Aptitude or interest in Automotive Engineering. ArcelorMittal Tailored Blanks is an Equal ...

ArcelorMittal

Data Analytics Co-Op

Detroit, MI

Data Analytics Co-Op Location: Detroit, MI Who Are We? Are you ready to be part of a dynamic and ... Aptitude or interest in Automotive Engineering. ArcelorMittal Tailored Blanks is an Equal ...

Venteon

Senior Director Data Analytics & AI

Novi, MI · On-site

Build, mentor, and lead high-performing global teams across data engineering, analytics, governance, and data science disciplines. * Establish scalable operating models and best practices for ...

next page

Showing results 1-20

All JobsData Analytics Engineer JobsData Analytics Engineer Jobs in Dearborn, MI

Data Analytics Engineer information

See Dearborn, MI salary details

$40.9K

$119.2K

$163.1K

How much do data analytics engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for data analytics engineer in Dearborn, MI is $119,172.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,200.00 and $126,300.00 per year, depending on experience, location, and employer.

How do data analytics engineers typically collaborate with data scientists and business stakeholders on projects?

Data Analytics Engineers play a crucial role in bridging the gap between raw data and actionable insights by building, optimizing, and maintaining data pipelines. They often work closely with data scientists to ensure data is clean, accessible, and structured for advanced analytics or machine learning models. Additionally, they collaborate with business stakeholders to understand reporting requirements and ensure that data solutions align with organizational objectives. Regular communication and cross-functional teamwork are essential aspects of this role, as engineers must translate business needs into technical specifications and deliver reliable data products.

What are the key skills and qualifications needed to thrive as a data analytics engineer, and why are they important?

To thrive as a Data Analytics Engineer, you need strong proficiency in data modeling, SQL, and statistical analysis, typically supported by a degree in computer science, statistics, or a related field. Familiarity with tools such as Python, R, Apache Spark, Tableau, and cloud data platforms like AWS or Google BigQuery is essential, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills help you translate data insights into actionable business solutions. These skills and qualities are crucial for designing robust data pipelines and enabling data-driven decision-making across organizations.

What is the difference between Data Analytics Engineer vs Data Scientist?

AspectData Analytics EngineerData Scientist
CredentialsBachelor's or master's in CS, Data Science, or related fields; certifications like Google Data AnalyticsBachelor's or master's in CS, Statistics, or related fields; certifications like Certified Data Scientist
Work EnvironmentFocus on building data pipelines, dashboards, and analytics toolsFocus on statistical modeling, machine learning, and data exploration
Employer & Industry UsageUsed across tech, finance, healthcare for data infrastructure and analyticsCommon in research, product development, and advanced analytics teams

While both roles work with data, Data Analytics Engineers primarily develop data infrastructure and tools for analysis, whereas Data Scientists focus on statistical modeling and machine learning to generate insights. They often collaborate but have distinct technical focuses.

What are the most commonly searched types of Data Analytics Engineer jobs in Dearborn, MI? The most popular types of Data Analytics Engineer jobs in Dearborn, MI are:
What are popular job titles related to Data Analytics Engineer jobs in Dearborn, MI? For Data Analytics Engineer jobs in Dearborn, MI, the most frequently searched job titles are:
What job categories do people searching Data Analytics Engineer jobs in Dearborn, MI look for? The top searched job categories for Data Analytics Engineer jobs in Dearborn, MI are:
What cities near Dearborn, MI are hiring for Data Analytics Engineer jobs? Cities near Dearborn, MI with the most Data Analytics Engineer job openings:
Data Analytics Engineer jobs near you
Infographic showing various Data Analytics Engineer job openings in Dearborn, MI as of August 2026, with employment types broken down into 100% Full Time. Highlights an 73% In-person, and 27% Remote job distribution, with an average salary of $119,172 per year, or $57.3 per hour.

12V Battery - Data Analytics Engineer

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 13 days ago

Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers

Job description

Stellantis is seeking a Warranty Data Analytics Engineer to join the Electrical & Hardware Engineering In-Field Quality organization. The successful candidate will be responsible for identifying, investigating, and resolving in-field quality issues related to 12V Battery systems. This role plays a key part in enhancing customer satisfaction and reducing warranty claims by delivering timely root cause analysis, corrective actions, and preventative measures in collaboration with engineering and cross-functional teams. The data analytics engineer is fundamental to providing customized data aggregations that the quality team can leverage to perform triage investigations and statistical tracking of corrective actions.
This Quality Engineer role is ideal for candidates who are hands-on, technically curious, and passionate about delivering high-quality automotive products to customers. It offers the opportunity to work in a fast-paced, cross-functional environment and directly impact the customer ownership experience across Stellantis brands. Reliability, availability, and passion to deliver are characteristics the candidate is expected to demonstrate on a daily basis.
Key Responsibilities:
  • Monitor fleet and field data (warranty, connected vehicle data, CAN network logs) to detect emerging electrical issues across the Stellantis North America fleet.
  • Develop custom data sets to support identification of specific issue signatures defined by the engineering team
  • Collaborate with Quality to support their ability to properly classify 12V Battery related issues
  • Develop tools to analyze the various facets of 12V Battery / vehicle system quality.
  • Track and document issue status in relevant systems (i.e. GIMs) and ensure timely resolution and communication of progress.
  • Support validation and verification testing to ensure effectiveness of implemented fixes.
  • Support the Quality Management Leader with data analysis, reporting, and field performance reviews.

Basic Qualifications:
  • Bachelor's degree in Electrical Engineering from an ABET accredited university
  • Minimum of 5 years of experience in data engineering or quality roles
  • Strong analytical and problem-solving skills with a solid foundation in root cause analysis
  • Experience with Palantir and Databricks
  • Strong interpersonal skills and ability to collaborate across functional teams
  • Excellent verbal and written communication skills

Preferred Qualifications:
  • Master's degree in Electrical, Mechanical, or Computer Engineering
  • Familiarity with structured problem-solving tools such as 8D, FMEA, Fault Tree, Red X, or Shainin
  • Experience in field issue resolution or warranty reduction projects
  • Proficiency with diagnostic tools and data logging systems
  • Experience using quality analytics platforms such as Palantir
  • Knowledge of Stellantis internal tools and systems: Quantic, QFS, CDA tool, JDP, CNs, GIMs
  • Green Belt certification or other formal quality training

What Stellantis employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply