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Remote Data Platform Engineer Jobs in Michigan (NOW HIRING)

Principal Data Engineer

Ann Arbor, MI ยท On-site +1

$170K - $210K/yr

Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data ... We're looking for a Principal Data Engineer to own the technical direction and execution of our ...

Security Platform Engineer

Dearborn, MI ยท On-site +1

$120.35K - $190.50K/yr

... Platform Engineering or a related field and 4 years of experience in the job offered or a related ... and defining data models to protect user identities and access policies. 2. Developing and ...

GCP Engineer

Detroit, MI ยท On-site +1

Develop and support cloud-based data pipelines, platform components, and environment setup ... remote client service delivery. Recruiting for this role ends on 06/30/2026. Work you'll do As a ...

Platform Software Engineer

Dearborn, MI ยท On-site +1

$140.63K - $188.56K/yr

Redefining mobility requires quality data, metrics, and analytics, as well as insightful ... Platform Software Engineer - positions offered by Ford Motor Company (Dearborn, Michigan). Note ...

Senior Data Engineer

Grand Rapids, MI ยท On-site +1

$101.80K - $138.30K/yr

At CertifID, we take this threat seriously and provide a secure platform that verifies the ... Remote worker reimbursement of $300/year * Professional development reimbursement * Competitive pay

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Remote Data Platform Engineer information

See Michigan salary details

$38.8K

$113.1K

$154.7K

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

As of May 29, 2026, the average yearly pay for remote data platform 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 are the key skills and qualifications needed to thrive as a Remote Data Platform Engineer, and why are they important?

To thrive as a Remote Data Platform Engineer, you need expertise in data engineering, database management, and cloud platforms, usually supported by a degree in computer science or a related field. Familiarity with tools such as SQL, Python, Spark, AWS, Azure, and certifications like AWS Certified Data Analytics are highly valued. Strong problem-solving, communication, and self-motivation skills help you excel in remote, collaborative environments. These skills and qualities ensure the efficient design, operation, and scaling of robust data platforms that drive business insights and operations.

What are the typical collaboration methods for a Remote Data Platform Engineer working with cross-functional teams?

As a Remote Data Platform Engineer, you will frequently collaborate with data scientists, analysts, and software engineers through virtual meetings, project management tools, and shared documentation platforms. Effective communication is essential, as much of the teamwork happens asynchronously using tools like Slack, Jira, and Confluence. You may participate in regular stand-ups, sprint planning, and code reviews to ensure alignment across the team. Building strong relationships remotely often involves proactive updates and clear documentation to keep all stakeholders informed and projects moving smoothly.

What is a Remote Data Platform Engineer?

A Remote Data Platform Engineer is a professional who designs, builds, and manages large-scale data infrastructure and platforms, while working remotely. They are responsible for ensuring data is efficiently collected, stored, processed, and made accessible for analysis, often using cloud technologies and big data tools. These engineers collaborate with data scientists, analysts, and other engineers to maintain data pipelines and optimize system performance. Their work enables organizations to leverage data for business insights, all while enjoying the flexibility of remote work.

What is the difference between Remote Data Platform Engineer vs Data Engineer?

AspectRemote Data Platform EngineerData Engineer
CredentialsBachelor's in CS, Data Science, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentRemote or hybrid, collaborating with data teams and cloud providersOn-site or remote, focusing on data pipelines and infrastructure
Industry UsageTech, finance, healthcare, and other data-driven sectorsSame industries, often overlapping roles
Search & Comparison IntentHigh overlap, often searched together due to similar skills

The Remote Data Platform Engineer focuses on building and maintaining cloud-based data platforms, ensuring scalability and performance. Data Engineers develop and manage data pipelines, databases, and ETL processes. While roles overlap in skills and industries, the Platform Engineer emphasizes cloud infrastructure, whereas Data Engineers concentrate on data processing and storage.

What are the most commonly searched types of Data Platform Engineer jobs in Michigan? The most popular types of Data Platform Engineer jobs in Michigan are:
What are popular job titles related to Remote Data Platform Engineer jobs in Michigan? For Remote Data Platform Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Data Platform Engineer jobs in Michigan look for? The top searched job categories for Remote Data Platform Engineer jobs in Michigan are:
What cities in Michigan are hiring for Remote Data Platform Engineer jobs? Cities in Michigan with the most Remote Data Platform Engineer job openings:
Infographic showing various Remote Data Platform Engineer job openings in Michigan as of May 2026, with employment types broken down into 1% Internship, 71% Full Time, 17% Part Time, 1% Temporary, 9% Contract, and 1% Nights. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $113,060 per year, or $54.4 per hour.

Google Cloud Platform Data Architect

Reliable Software Resources

Detroit, MI โ€ข Remote

$58.25 - $75/hr

Other

Posted yesterday


Job description

Job Role: Google Cloud Platform Data Architect

Location: Detroit, MI

Hire-type: Contract

Experience: 8+ yearsย  |ย  Detroit, MI (mandatory) โ€” Remote up to 50% travelย ย 

Python

Google Cloud Platform Native

Data Warehousing

BigQuery

Data Modeling

ETL / ELT Pipelines

ABOUT THE ROLE

As a Google Cloud Platform Data Architect at DataFactZ you will own the end-to-end design of cloud-native data warehouse and data platform solutions on Google Cloud. You will define data architecture standards, establish data modeling patterns, and lead the design of scalable ingestion and transformation pipelines โ€” working hands-on with engineering teams to deliver production-grade data systems for enterprise clients.

ย 

KEY RESPONSIBILITIES

โ€ขย ย ย ย ย ย Architect enterprise data warehousing solutions on Google Cloud Platform using BigQuery as the primary analytical platform, including logical and physical data model design

โ€ขย ย ย ย ย ย Design and implement data modeling patterns:ย star schema, snowflake, data vault, and wide-table approaches optimized for BigQuery performance and cost

โ€ขย ย ย ย ย ย Define lakehouse architectures across BigQuery and Cloud Storage using Parquet, Avro, and ORC formats with appropriate partitioning and clustering strategies

โ€ขย ย ย ย ย ย Lead the design of batch and streaming ingestion pipelines using Dataflow (Apache Beam), Dataproc (PySpark), Pub/Sub, and BigQuery Data Transfer Service

โ€ขย ย ย ย ย ย Establish transformation layer standards using dbt or Python-based ELT patterns within BigQuery

โ€ขย ย ย ย ย ย Design pipeline orchestration frameworks using Cloud Composer (Airflow) for complex multi-step workflows

โ€ขย ย ย ย ย ย Define data governance standards:ย schema management, data lineage, access controls, and partitioning policies across Google Cloud Platform projects

โ€ขย ย ย ย ย ย Lead technical discovery with client stakeholders, produce architecture decision records, and translate business requirements into data platform designs

โ€ขย ย ย ย ย ย Mentor data engineers and ensure adherence to architecture standards across delivery teams

ย 

REQUIRED SKILLS

โ€ขย ย ย ย ย ย Python:ย Advanced proficiency for pipeline development, data transformation scripts, and Google Cloud Platform SDK/API integrations

โ€ขย ย ย ย ย ย Google Cloud Platform expertise:ย Deep hands-on experience with BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and Cloud SQL

โ€ขย ย ย ย ย ย Data warehousing:ย Proven experience designing enterprise-scale data warehouses with dimensional and vault modeling techniques

โ€ขย ย ย ย ย ย Data modeling:ย Strong ability to design logical and physical models for analytical and operational workloads on BigQuery

โ€ขย ย ย ย ย ย ETL/ELT pipelines:ย Designing and overseeing large-scale batch and streaming data pipelines for structured and semi-structured data

โ€ขย ย ย ย ย ย SQL:ย Expert-level BigQuery SQL including window functions, nested/repeated fields, partitioning, and query optimization

โ€ขย ย ย ย ย ย Leadership:ย Ability to lead architecture decisions, align cross-functional teams, and mentor engineers

ย 

PREFERRED

โ€ขย ย ย ย ย ย Google Cloud Platform certifications:ย Professional Data Engineer or Professional Cloud Architect

โ€ขย ย ย ย ย ย Experience with dbt Cloud for BigQuery transformation and documentation

โ€ขย ย ย ย ย ย Familiarity with data catalog tools:ย Dataplex, Data Catalog, or Collibra on Google Cloud Platform

โ€ขย ย ย ย ย ย Exposure to real-time analytics patterns using BigQuery streaming inserts or Bigtable