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Quantitative Data Engineer Jobs in Michigan (NOW HIRING)

Data Engineer with DevOps Skill

Dearborn, MI · On-site

$105K - $126K/yr

Education & Experience: · Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related quantitative field. · Typically, 8+ years of experience in data ...

Two plus (2+) years of experience involving quantitative data analyses for problem solving in US Healthcare industry. * One plus (1+) year experience working with cloud Big Data Stack to orchestrate ...

Master's degree in quantitative fields, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science or equivalent combination of ...

Overview: Business and Data Analysts work closely with data engineers, data scientists, and ... Bachelor's degree in a quantitative field (e.g., Statistics, Economics, Mathematics, Computer ...

Knowledge of Comerica data and processes preferred * Advanced degree in quantitative analytics, economics, statistics, engineering, or a related area. * Minimum 4-5 years of experience in statistical ...

Master's degree in Data Science, Computer Science, Computer Engineering, Statistics, or a related highly quantitative field. * Experience: 5+ years of combined experience in Data Science, Data ...

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Quantitative Data Engineer information

What are the key skills and qualifications needed to thrive as a Quantitative Data Engineer, and why are they important?

To excel as a Quantitative Data Engineer, you need strong proficiency in programming (such as Python, R, or C++), advanced mathematical and statistical knowledge, and a relevant degree in computer science, mathematics, or a related field. Experience with big data tools (like Spark, Hadoop), cloud platforms, and data pipeline systems, as well as familiarity with financial data sets, is typically required. Analytical thinking, detail orientation, and effective problem-solving skills distinguish top performers in this role. These competencies are critical for efficiently transforming complex data into actionable insights and supporting robust quantitative models in data-driven environments.

What is a Quantitative Data Engineer?

A Quantitative Data Engineer is a professional who designs, builds, and maintains data infrastructure that supports quantitative analysis, typically in finance or technology sectors. They work closely with quantitative analysts and data scientists to ensure efficient data pipelines, data quality, and high-performance systems for processing large datasets. Their responsibilities include developing ETL processes, optimizing databases, and implementing data models to support research and trading strategies. Strong programming skills, expertise in big data technologies, and knowledge of quantitative methods are essential for this role.

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

AspectQuantitative Data EngineerData Scientist
Primary FocusBuilding data pipelines, data infrastructure, and ensuring data qualityAnalyzing data, creating models, and deriving insights
Skills & ToolsSQL, Python, Spark, ETL processes, data architectureStatistics, machine learning, Python/R, data visualization
CredentialsComputer science, engineering, or related degrees; certifications in data engineeringStatistics, data science, or related degrees; certifications in data analysis or machine learning
Work EnvironmentData engineering teams, data infrastructure projectsData analysis teams, research, and modeling projects

While both roles work closely with data, Quantitative Data Engineers focus on building and maintaining data systems, whereas Data Scientists analyze data to generate insights and models. They often collaborate but have distinct skill sets and responsibilities within data-driven organizations.

How does a Quantitative Data Engineer typically collaborate with data scientists and quantitative analysts on projects?

Quantitative Data Engineers work closely with data scientists and quantitative analysts to design, build, and optimize data pipelines that support complex modeling and analytics. They are often responsible for ensuring data quality, scalability, and efficient data processing, enabling analysts to focus on developing models and extracting insights. Regular collaboration includes translating analytical requirements into technical solutions, troubleshooting data issues, and iterating on data infrastructure to support evolving project needs. This teamwork fosters an environment where technical and analytical expertise complement each other, leading to more robust and actionable results.
What are popular job titles related to Quantitative Data Engineer jobs in Michigan? For Quantitative Data Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Quantitative Data Engineer jobs in Michigan look for? The top searched job categories for Quantitative Data Engineer jobs in Michigan are:
What cities in Michigan are hiring for Quantitative Data Engineer jobs? Cities in Michigan with the most Quantitative Data Engineer job openings:
Infographic showing various Quantitative Data Engineer job openings in Michigan as of July 2026, with employment types broken down into 1% As Needed, 80% Full Time, 10% Part Time, 8% Contract, and 1% Nights. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution.

Connected Vehicle Data Engineer

Ford Motor Company

Dearborn, MI

$105K - $127K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 10 days ago


Job description

We made history and now we work to transform the future - for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.


Product Development uses design thinking & user experience methods to deliver breakthrough products and services that delight our customers. We bring innovative, exciting, and sustainable ideas to life.We have opportunities around the world for you to contribute to advancements in autonomy, electrification, smart mobility technologies, and more!

You'll have...

  • Bachelor's Degree in Engineering, Data Science, Computer Science, Statistics, or a related quantitative field.
  • 3+ years of analytical, querying, and programming experience (SQL, Python, PySpark/Spark, and similar big data tools).

Even better, you may have...

  • Master's Degree or Ph.D. in Engineering, Data Science, Statistics, Machine Learning, or a similar quantitative field.
  • 2+ years of experience in the automotive industry (Product Development, Calibration, and/or Quality).
  • Proven experience building and applying Machine Learning models (such as supervised/unsupervised learning, regression, classification, or anomaly detection) to solve physical systems or engineering problems.
  • 5+ years of propulsion systems experience with a strong understanding of delivering calibration processes.
  • 2+ years of experience in the Connectivity eco-system, delivering big data analytics projects from concept to production.
  • Strong knowledge of statistical inference, risk quantification methods, and reliability engineering.
  • Experience with Agile methodologies, Git version control, and CI/CD pipelines for ML models (MLOps).
  • Ability to write sophisticated, optimized SQL queries to extract and transform massive, unstructured CV datasets.
  • Ability to take complex, ambiguous engineering problems and break them down to build, prioritize, and implement actionable data science solutions.
  • Exceptional communication and visualization skills, with the ability to build intuitive dashboards (e.g., Looker,  PowerBI) to enable inference and decision-making by customers and stakeholders.
  • Strong team player with proven experience and a willingness to take ownership of a topic and successfully bring it to completion.
  • Google Cloud Platform (GCP) or Professional Data Engineer/Machine Learning Engineer Certification.

What you'll do...

  • Apply Machine Learning to Powertrain Data: Develop, train, and deploy machine learning models on curated powertrain data to detect anomalies, identify early-warning quality indicators, and predict component degradation.

  • Quantify & Assess Risk: Use statistical modeling and ML inference to quantify, assess, and prioritize risks associated with powertrain field quality issues, enabling data-driven decision-making.

  • Perform Inferential Analytics: Conduct inferential and diagnostic analytics to identify root causes of complex engineering and quality problems, translating CV big data into actionable insights.

  • Establish Stakeholder Alignment: Build strong working relationships with key stakeholders in Product Development to ensure that plans and requirements are fully understood, and issues are resolved effectively and efficiently.

  • Debug & Resolve Issues: Debug, root-cause, and resolve propulsion systems quality issues with cross-functional teams, leveraging connected vehicle data, ML models, and enterprise toolsets.
    Foster Data Collection: Drive and optimize connected vehicle data collection strategies for solving engineering problems and characterizing customer usage patterns.

  • Query & Manipulate Big Data: Write highly proficient BigQuery SQL (and similar language) queries to extract, clean, and interpret massive, connected vehicle datasets in the propulsion systems domain.
    Develop Data Pipelines: Design, build, and own robust data pipelines and workflows using Python, PySpark, and modern data engineering tools to support ML model training and deployment.

  • Coordinate Data Creation: Partner with vehicle software teams to define and create new connected vehicle data elements, and support the validation of these new telemetry signals.

  • Validate via Calibration Tools: Utilize in-vehicle calibration tools (ATI / ETAS) to collect high-frequency data to validate connected data and verify ML model predictions on key propulsion features and subsystems.

  • Synthesize & Communicate Insights: Summarize and present complex machine learning models, statistical analyses, and big data findings in a simplified, visual fashion to both technical and non-technical audiences, including executive leadership.

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above?

No matter what you choose, we offer a work life that works for you, including:

  • Immediate medical, dental, vision and prescription drug coverage

  • Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more

  • Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more

  • Vehicle discount program for employees and family members and management leases

  • Tuition assistance

  • Established and active employee resource groups

  • Paid time off for individual and team community service

  • A generous schedule of paid holidays, including the week between Christmas and New Year's Day

  • Paid time off and the option to purchase additional vacation time.
     

This position is a salary grade 5 and ranges from $65,100-$109,300

This position is a salary grade 6 and ranges from $74,300-$124,500

This position is a salary grade 7 and ranges from $86,600-$144,900

This position is a salary grade 8 and ranges from $99,100-$166,200


Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
For more information on salary and benefits, click here: https://fordcareers.co/GSR

Visa sponsorship is not available for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week.

   #LI-JF1 #VehicleHardwareEngineering #Hybrid
 


Ford logo

About Ford

Sourced by ZipRecruiter

At Ford Motor Company, we believe freedom of movement drives human progress. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career and help us define tomorrow's transportation.

Industry

Civil engineering construction

Company size

51 - 200 Employees

Headquarters location

Doral, FL, US

Year founded

1982