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Remote Data Engineering Jobs in Michigan (NOW HIRING)

Gordon Food Service

Intermediate Data Engineer

Wyoming, MI · On-site +1

$103K - $124K/yr

They need to have the ability to understand complex architecture and engineering designs and have ... Hybrid schedule, 4 days in office in Wyoming, MI or Atlanta, GA with 1 day remote What you'll bring ...

Vervint

Director of Data Intelligence

Grand Rapids, MI · On-site +1

Director of Data Intelligence | Remote | Michigan or Minnesota Preferred Role Snapshot: * Set the ... Build and lead a high-performing team of data scientists, analysts, and engineers. * Promote a ...

CSAA

Job Title Enterprise Data Architect - Remote Requisition Number R7730 Enterprise Data Architect ... Solutions are built in a highly collaborative environment, partnering with engineering, product ...

Ford Motor Company

Data Engineer

Dearborn, MI · On-site +1

$140K - $184K/yr

Data Engineer - positions offered by Ford Motor Company (Dearborn, Michigan). Note, this is a hybrid position whereby the employee will work both from home and from the anticipated worksite. Hence ...

General Motors

Senior AI/ML Engineer

Lansing, MI · On-site +1

$106K - $145K/yr

Remote/Hybrid: This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA ... The Data Labeling Engineering team designs, builds, and operates hybrid human/machine data labeling ...

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All JobsRemote Data Engineering JobsRemote Data Engineering Jobs in Michigan

Remote Data Engineering information

See Michigan salary details

$38.8K

$113.1K

$154.7K

How much do remote data engineering jobs pay per year?

As of Jun 20, 2026, the average yearly pay for remote data engineering 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.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote data engineers often work with distributed teams, which requires strong communication and organization skills. They collaborate using tools like Slack, Zoom, and project management platforms to stay aligned on data pipeline development, troubleshooting, and deployment. Regular stand-ups, asynchronous documentation, and clear communication of progress are essential for ensuring everyone is on the same page, regardless of location. Flexibility in working hours and proactive scheduling of meetings help facilitate effective collaboration and project delivery.

What is remote data engineering?

Remote data engineering involves designing, building, and maintaining data systems and pipelines while working from a location outside of a traditional office. Remote data engineers use tools to collect, process, and store large sets of data, making it accessible for analysis and business decision-making. They collaborate with teams virtually, often using cloud-based technologies, to ensure that data infrastructure is reliable, scalable, and secure. This role requires strong technical skills in programming, databases, and data architecture, as well as the ability to communicate effectively in a distributed work environment.

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

To thrive as a Remote Data Engineer, you need strong programming skills (such as Python, Java, or Scala), experience with data modeling, ETL processes, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Proficiency with big data tools like Apache Spark, Hadoop, cloud platforms (AWS, Azure, GCP), and certifications in these technologies is highly valued. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These competencies ensure effective data pipeline development, reliable data management, and seamless teamwork across distributed environments.

What is the difference between Remote Data Engineering vs Remote Data Analyst?

AspectRemote Data EngineeringRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with SQL, Python, cloud platformsBachelor's in Statistics, Data Science, or related; proficiency in Excel, SQL, visualization tools
Work EnvironmentBuilds data pipelines, manages databases, works with cloud infrastructureAnalyzes data sets, creates reports, visualizes data insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, finance, retail, consulting

Remote Data Engineering focuses on designing and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require strong analytical skills but differ in technical depth and responsibilities.

What are the most commonly searched types of Data Engineering jobs in Michigan? The most popular types of Data Engineering jobs in Michigan are:
What are popular job titles related to Remote Data Engineering jobs in Michigan? For Remote Data Engineering jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Data Engineering jobs in Michigan look for? The top searched job categories for Remote Data Engineering jobs in Michigan are:
What cities in Michigan are hiring for Remote Data Engineering jobs? Cities in Michigan with the most Remote Data Engineering job openings:
Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in Michigan as of June 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.

Azure Databricks Architect

Reliable Software Resources

Detroit, MI • Remote

$58 - $75.75/hr

Other

Posted 2 days ago

Job description

Job Role: Azure Databricks Architect
Location: Remote and Travel
Hire-Type: Long-term
 
 
 
Key Responsibilities
Responsibilities below apply across the team. Individual engineers own the areas aligned to their role above.
  • Security Platform — Pipeline Operations & Data Quality
  • Security Platform — Customer Enablement
  • Security Platform — New Source Onboarding
  • Security Platform — Pipeline Development
  • SOX Platform — Source Onboarding & Pipeline Management
  • SOX Platform — Alert Management
  • SOX Platform — Monitoring Team Support
  • SOX Platform — Audit Support & Evidence
  • SOX Platform — Application Development & Release Management
  • Cross-Platform Responsibilities
Required Qualifications
Experience
  • 5+ years of data engineering experience with at least 2 years on Azure Databricks or equivalent cloud lakehouse platforms.
  • Hands-on experience with Medallion Architecture pipelines, Delta Lake (MERGE, OPTIMIZE, VACUUM, Z-ORDER, schema enforcement), and Databricks Structured Streaming.
  • Familiarity with SOX compliance, IT General Controls (ITGC), or regulated-environment data engineering; experience supporting audits or evidence collection.
Security Domain Knowledge
  • Familiarity with OCSF (Open Cybersecurity Schema Framework) or willingness to develop deep expertise rapidly.
  • Understanding of security log source types (EDR, firewall, IAM/PAM, CASB) and SOC/SIEM/SOAR workflows; awareness of MITRE ATT&CK framework.
Preferred Qualifications
  • OCSF normalization implementation across multiple security log sources.
  • Experience with Azure API Management (APIM) for data platform API governance.
  • UEBA, threat scoring, or ML-backed security analytics (MLflow, Databricks Feature Store, Mosaic AI).
  • SOX audit participation — auditor walkthroughs, evidence packages, IT General Controls testing.
  • Certifications: Databricks Certified Data Engineer Associate/Professional, Azure Data Engineer Associate (DP-203), or equivalent.
  • Graph-based correlation (Databricks GraphX); Delta Sharing.
 

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