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Remote Azure Data Engineer Jobs in Michigan (NOW HIRING)

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

CSAA

You will partner with Data Engineering, Data Science, Architecture, Infrastructure, Security, and ... We embrace a remote-first culture through our Flexible Workplace. Most employees hold Home-Flex ...

Munich Re

Data Scientist

Ann Arbor, MI · On-site +1

... Azure DevOps. Skills / Knowledge / Experience: * Develop and project manage modeling projects and ... Data Scientist: 2 or more years of data science/predictive analytics experience in (re)insurance or ...

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Remote Azure Data Engineer information

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How much do remote azure data engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote azure data engineer in Michigan is $113,060.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $119,800.00 per year, depending on experience, location, and employer.

What is a remote Azure Data Engineer?

A Remote Azure Data Engineer is responsible for designing, implementing, and managing data solutions using Microsoft Azure cloud services while working from a remote location. They work with tools like Azure Data Factory, Azure SQL Database, and Azure Synapse Analytics to process, store, and analyze data. Their role includes data pipeline development, performance optimization, and ensuring data security. Collaboration with data scientists, analysts, and business teams is common to support data-driven decision-making.

What are the key skills and qualifications needed to thrive as a remote Azure Data Engineer?

To thrive as a Remote Azure Data Engineer, you need expertise in designing, implementing, and managing data solutions using Microsoft Azure, along with proficiency in SQL, data warehousing, and ETL processes. Familiarity with tools like Azure Data Factory, Azure SQL Database, Databricks, and certifications such as Microsoft Certified: Azure Data Engineer Associate are highly valued. Strong problem-solving skills, effective communication, and the ability to work autonomously make candidates stand out in this remote role. These skills ensure that data pipelines are robust, secure, and scalable, enabling organizations to make data-driven decisions efficiently.

What are some common challenges a remote Azure Data Engineer might face, and how are they typically addressed?

A common challenge for Remote Azure Data Engineers is ensuring secure, reliable data transfer and integration across distributed systems while collaborating with teams that may be in different time zones. This is typically addressed by implementing best practices for cloud security, employing automated monitoring, and leveraging project management tools to stay aligned with cross-functional teams. Clear, proactive communication is essential in a remote environment, as is documentation to keep everyone updated on project progress. Many organizations also offer regular virtual check-ins and access to knowledge-sharing platforms to foster collaboration. By staying organized and proactive, remote Azure Data Engineers can successfully deliver scalable data solutions in a distributed work setup.

What are the most commonly searched types of Azure Data Engineer jobs in Michigan?

The most popular types of Azure Data Engineer jobs in Michigan are:

What are popular job titles related to Remote Azure Data Engineer jobs in Michigan?

For Remote Azure Data Engineer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Azure Data Engineer jobs in Michigan look for?

The top searched job categories for Remote Azure Data Engineer jobs in Michigan are:

What cities in Michigan are hiring for Remote Azure Data Engineer jobs?

Cities in Michigan with the most Remote Azure Data Engineer job openings:

Remote Azure Data Engineer jobs near you
Infographic showing various Remote Azure Data Engineer job openings in Michigan as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $113,060 per year, or $54.4 per hour.

Data Scientist

Ford Motor Company

Dearborn, MI • Remote

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 22 days ago

Ford Motor Company rating

7.6

Company rating: 7.6 out of 10

Based on 527 frontline employees who took The Breakroom Quiz

11th of 45 rated automakers

Job description

The Senior Data Scientist will design and implement advanced systems that support cross-domain manufacturing analytics. This role operates at the intersection of optimization, enterprise data integration, and applied analytics to enable data-driven decision-making across complex business workflows.

Key responsibilities include:

  • Developing and maintaining Python-based optimization models to support demand elasticity, production planning, and constraint-based decision frameworks.

  • Integrating heterogeneous enterprise datasets into structured, analysis-ready pipelines using BigQuery, GCS, and Python.

  • Performing data reconciliation, fuzzy matching, and standardization across inconsistent source systems to ensure data quality and analytical integrity.

  • Designing and deploying lightweight internal applications (e.g., Dash-based tools) and contributing to containerized deployments to enable business-facing access to decision models.

  • Collaborating with cross-functional stakeholders to translate business questions into optimization and analytical frameworks.

In addition, this role will contribute to the development of semantically aligned data structures by supporting feature definition consistency, cross-system mapping, and ontology-informed modeling approaches. The candidate will help ensure that analytical outputs are built on clearly defined entities, relationships, and assumptions to enable scalable reasoning and reuse across domains.

The ideal candidate combines strong technical modeling capability with practical enterprise data engineering experience and the ability to operate effectively in ambiguous, cross-functional environments.

  • Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research, or equivalent field.

  • 3+ years of experience developing analytical or optimization models in Python.

  • Experience building and maintaining data pipelines using SQL and cloud-based data platforms (e.g., BigQuery, GCS).

  • Strong proficiency in Python for data analysis and modeling (e.g., pandas, NumPy, Pyomo or similar optimization libraries).

  • Experience integrating and standardizing heterogeneous enterprise datasets.

  • Familiarity with containerization concepts (e.g., Docker) and deploying lightweight applications or services in a cloud environment.

  • Ability to translate business problems into structured analytical frameworks.

  • Strong written and verbal communication skills with experience working cross-functionally.

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.
 
For a detailed look at our benefits, click here: Benefit Summary
 
 
This role is remote but if you live within 50 miles within Dearborn, MI, you will be required on-site 4x a week.
 
*Visa Sponsorship IS provided for this specific role*
*Relocation assistance IS provided for this specific 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-Remote
#LI-DS2 
 
SG7-8

  • Design, develop, and maintain Python-based optimization models to support demand elasticity, production planning, and constraint-based decision systems.

  • Translate complex business problems into structured analytical and optimization frameworks.

  • Build and maintain data pipelines using BigQuery, GCS, and Python to integrate heterogeneous enterprise data sources.

  • Perform data reconciliation, fuzzy matching, and standardization across inconsistent datasets to ensure analytical integrity.

  • Develop lightweight internal applications (e.g., Dash or streamlit) to operationalize analytical outputs for business users.

  • Contribute to containerized deployments to support scalable and maintainable delivery of decision tools.

  • Partner with cross-functional stakeholders to define requirements and validate outputs.

  • Support semantic alignment across systems by contributing to feature definition consistency, cross-system mapping, and ontology-informed data structures.

  • Document modeling assumptions, data transformations, and system dependencies to enable reproducibility and reuse.

  • Continuously improve model performance, data quality, and deployment efficiency across decision systems.

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