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Quantitative Data Engineer Jobs in Michigan (NOW HIRING)

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

... or a related quantitative field is preferred. Experience: 5+ years of professional experience in data engineering, data-platform engineering, analytics engineering, or a related discipline.

Data Engineer

Dearborn, MI · On-site

$105K - $127K/yr

Master's degree in Computer Science, Data Engineering, Analytics, or a related quantitative field is preferred. Experience: * 5+ years of professional experience in data engineering, data-platform ...

Data Engineer

Dearborn, MI · On-site

$105K - $127K/yr

Master's degree in Computer Science, Data Engineering, Analytics, or a related quantitative field is preferred. Experience: * 5+ years of professional experience in data engineering, data-platform ...

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 ...

$103K - $124K/yr

Bachelor's or Master's degree in Data Science, Computer Engineering, Industrial Engineering, Automation, or a related quantitative field. * Strong knowledge of SQL, Power BI, SharePoint 365, and ...

Data scientists work closely with data engineers, analysts, and business teams to design analytics ... Bachelor's degree in a quantitative discipline (e.g., Statistics, Economics or other quantitative ...

AI and Data Science Engineer II

Detroit, MI

$113K - $136K/yr

... another quantitative field * 2+ years of industry experience outside of academia applying data ... Master's degree in engineering, mathematics, physics, machine learning, statistics, computer ...

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

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

Optical Engineer

Southfield, MI · On-site

$118K - $153K/yr

Analyze complex optical performance issues, use quantitative data to determine root cause, and ... Mentor engineers and technicians in optical measurement techniques, data interpretation, laboratory ...

Optical Engineer

Southfield, MI · On-site

$118K - $153K/yr

Analyze complex optical performance issues, use quantitative data to determine root cause, and ... Mentor engineers and technicians in optical measurement techniques, data interpretation, laboratory ...

Optical Engineer

Southfield, MI · On-site

$118K - $153K/yr

Analyze complex optical performance issues, use quantitative data to determine root cause, and ... Mentor engineers and technicians in optical measurement techniques, data interpretation, laboratory ...

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Quantitative Data Engineer information

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.

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 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 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.

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 August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Engineer

Dearborn, MI • On-site

Ford Motor Company
Motor Vehicle Manufacturing • 10K+ employees

$105K - $126K/yr

Full-time

Medical, Dental, Life, PTO

Re-posted 25 days ago


Ford Motor Company rating

7.6

Company rating: 7.6 out of 10

Based on 529 frontline employees who took The Breakroom Quiz


Job description

The Pro360 team is tasked with creating a seamless, data-driven ecosystem for Ford Pro. In this role, you will be responsible for the end-to-end data lifecycle-from ingestion and transformation to visualization and executive presentation. You will work within a modern tech stack centered on the Google Cloud Platform, utilizing your expertise in SQL and Python to build scalable pipelines.

Uniquely, this role bridges the gap between traditional data engineering and DevOps, as you will manage infrastructure using Terraform and Tekton. Beyond the technical build, you will act as a consultant to the business, using Looker Studio and the Microsoft Office suite to present insights that influence strategic decisions at management level. Design, develop, maintain, and optimize complex data pipelines using Astronomer, Apache Airflow, and related orchestration technologies.

Build scalable data ingestion, transformation, validation, and processing solutions across structured and semi-structured data sources. Deploy and manage cloud-based data services on Google Cloud Platform, including BigQuery, Dataflow, and Cloud Run. Write advanced SQL queries to extract, transform, analyze, and optimize large-scale datasets.

Develop clean, maintainable Python code for data transformation, automation, workflow development, and analysis. Design and support data models, datasets, and reporting layers that enable trusted business intelligence and analytics. Use Terraform to provision and manage cloud infrastructure through Infrastructure as Code practices.

Build and maintain CI/CD automation using Tekton, GitHub, and related DevOps tools. Implement data-quality controls, monitoring, error handling, and operational-support practices to ensure pipeline reliability and data accuracy. Build intuitive dashboards and reporting solutions in Looker Studio to track key performance indicators and provide visibility to business stakeholders.

Partner with business teams and leadership to understand data needs, define reporting requirements, and align data strategy with business goals. Translate technical findings and complex data insights into clear, concise, and actionable presentations for non-technical audiences. Use Microsoft Office tools, including PowerPoint and Excel, to develop executive-ready analyses, reports, and presentations.

Participate in technical design sessions, Agile planning, peer reviews, and continuous-improvement activities. Contribute to data-engineering standards, documentation, reusable development patterns, and a collaborative engineering culture. We recognize that no one person will embody every single quality or skill listed below.

If you are passionate about data engineering, cloud platforms, automation, and delivering meaningful business insights, we encourage you to apply. Education: Requires a bachelor's or foreign equivalent degree in computer science, information technology or a technology related field Master's degree in Computer Science, Data Engineering, Analytics, or a related quantitative field is preferred. Experience: 5+ years of professional experience in data engineering, data-platform engineering, analytics engineering, or a related discipline.

Experience designing, building, deploying, and supporting scalable data pipelines and cloud-based data solutions. Experience working with business stakeholders to translate data requirements into technical solutions and actionable insights. Strong communication, analytical, problem-solving, and stakeholder-management skills.

Ability to work independently and collaboratively within a cross-functional, Agile delivery environment. Required Technical Experience: Strong SQL skills, including the ability to write complex queries, optimize performance, and manage large-scale datasets. Hands-on experience with BigQuery and PostgreSQL database technologies, including pgAdmin or comparable database-management tools.

Intermediate to advanced Python coding skills, with experience developing clean, maintainable code for data manipulation, automation, and analysis. Hands-on Google Cloud Platform experience, including BigQuery, Dataflow, and Cloud Run. Experience designing and managing data-pipeline orchestration using Apache Airflow, Astronomer, or similar technologies.

Experience using Terraform for cloud-infrastructure provisioning and Infrastructure as Code. Experience using Tekton or comparable CI/CD technologies to automate data-platform deployment and release processes. Experience using GitHub and modern development tools, including Visual Studio Code, for version control and collaborative development.

Experience building business dashboards and visualizations using Looker Studio or similar business-intelligence tools. Understanding of data quality, data governance, cloud security, monitoring, and operational-support practices. Preferred Experience: Experience with additional GCP services relevant to data engineering, analytics, and application development.

Experience processing high-volume data using Apache Spark, Dataflow, or other distributed data-processing technologies. Familiarity with data modeling, data warehousing, and modern data-lakehouse architecture patterns. Experience developing executive dashboards, KPI reporting, and strategic business insights.

Experience with Microsoft Excel, PowerPoint, and other tools used for executive communications and data storytelling. Experience supporting Ford Pro, fleet-management, commercial-vehicle, mobility, or customer-productivity initiatives. Familiarity with Agile development methods, DevOps practices, automated testing, and cloud-native engineering principles.

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, and prescription drug coverage Flexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care 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

For a detailed look at our benefits, click here: Benefit Summary This position is a salary grade 8. This position is a salary grade 8 and ranges from $115,000-$192,900. 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.

* Please note: This is a hybrid role, you are expected to relocate if you are not within commutable distance, and responsible to be onsite 4 days per week * *Visa Sponsorship is provided for this role* 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 committed to a culturally diverse workforce.

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. #LI-Hybrid #LI-GH2.


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