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Data Processor Jobs in Michigan (NOW HIRING)

Saransh Inc

GCP Data Engineer with Python

Dearborn, MI · On-site

$105K - $126K/yr

Exposure to Big Data ecosystems and distributed data processing. Nice to have Technical Skills: * Prior experience with ETL tools like DataStage or Informatica. Responsibilities: * The Data Engineer ...

Damco Solutions

Data Engineer (with NIKE exp.)

Dearborn, MI · On-site

$105K - $126K/yr

The role involves working with tools such as Hadoop, Spark, and Python to process and analyze large data sets. Qualifications : Required : • Linux • Hadoop • Hive • HQL (Hive Query Language ...

Corning

$104K - $125K/yr

... processes to improve data reliability and reduce production issues. - Lead the technical delivery of complex Data Engineering projects, including solution design, development, testing, deployment ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Design and implement complex data processing pipelines using Apache Spark. • Architectural Leadership: Build scalable, distributed systems that handle high-throughput data streams and large-scale ...

Converys

Data Architect

East Lansing, MI · On-site

$105K - $143K/yr

Lead the migration from legacy batch processes to automated, event-driven, or CDC-based ingestion patterns. * Implement data quality rules, validation frameworks, and reconciliation logic. * Optimize ...

KODE Labs

Data Engineer

Detroit, MI · On-site

$104K - $125K/yr

You will be at the forefront of processing and managing a high volume of data, handling billions of data points monthly to deliver insightful metrics and Key Performance Indicators (KPIs). Your ...

Ford Motor Company

Data Anchor

Dearborn, MI · On-site

Deep expertise in big data processing frameworks (e.g., Hadoop, Apache Spark, Kafka). * Hands-on experience with streaming data and Industrial IoT protocols, specifically MQTT. * Advanced database ...

MM International

Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

Design, develop, implement, and maintain robust integrations between WorkForce Software and various internal and external systems, ensuring seamless data flow and process synchronization. This ...

Technomics

Data Analyst

Troy, MI · On-site

Experience with PySpark, Spark, or other large-scale data processing technologies. * Experience integrating practical AI capabilities, such as LLMs or machine learning models, into user-facing ...

Technomics, Inc.

Data Analyst

Troy, MI · On-site

Experience with PySpark, Spark, or other large-scale data processing technologies. * Experience integrating practical AI capabilities, such as LLMs or machine learning models, into user-facing ...

Apex Systems

Google Cloud Platform Data Engineer

Dearborn, MI · On-site

$105K - $126K/yr

This role develops and optimizes data infrastructure, pipelines, and platforms that enable the efficient collection, storage, processing, and analysis of large volumes of structured and unstructured ...

KODE Labs

Staff Data Engineer - Energy Data

Detroit, MI · On-site

$104K - $125K/yr

Experience building scalable data pipelines and working with modern data processing and storage technologies. * Strong problem‑solving skills and the ability to translate complex data‑quality ...

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All JobsData Processor JobsData Processor Jobs in Michigan

Data Processor information

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How much do data processor jobs pay per hour?

As of Sep 11, 2026, the average hourly pay for data processor in Michigan is $17.66, according to ZipRecruiter salary data. Most workers in this role earn between $14.04 and $19.47 per hour, depending on experience, location, and employer.

What is a data processor?

A data processor transfers, organizes, and processes personal data for a company. It is typically an entry-level job that serves as a starting point for a career as a data controller. As a data processor, your duties involve processing incoming documents, transferring analog documents into digital data, verifying the information in all documents, updating document formats, and creating detailed reports on company data use and management. Qualifications for this career include excellent computer skills and a bachelor’s degree in computer science or data management.

What are the key skills and qualifications needed to thrive as a data processor, and why are they important?

To thrive as a Data Processor, you need strong attention to detail, accuracy in data entry, and a high school diploma or equivalent. Familiarity with spreadsheet software (such as Microsoft Excel), database management systems, and sometimes data processing software is typically required. Excellent organizational skills, the ability to follow procedures, and effective time management make someone stand out in this role. These skills ensure data integrity, minimize errors, and support efficient information management within an organization.

What are some common challenges faced by data processors and how can they be addressed?

Data Processors often encounter challenges such as managing large volumes of data accurately and efficiently, dealing with inconsistent or incomplete data, and ensuring data privacy and compliance. To address these, it's important to develop strong attention to detail, become proficient with data processing software, and stay updated on relevant data protection regulations. Collaborating closely with data analysts and IT teams can also help resolve data issues and improve workflow efficiency.

What is the difference between Data Processor vs Data Entry Clerk?

AspectData ProcessorData Entry Clerk
Required CredentialsHigh school diploma; some roles may require basic certificationsHigh school diploma; no specialized certifications typically needed
Work EnvironmentOffice settings, data centers, or remote workOffice environments, often in administrative settings
Employer & Industry UsageBusinesses, government agencies, financial institutionsCorporations, healthcare, retail, administrative offices
Common Search & ComparisonOften compared for data handling and processing tasksCompared for data input and administrative support roles

While both roles involve handling data, Data Processors typically perform more complex data management and validation tasks, often requiring some technical skills. Data Entry Clerks focus on inputting data accurately and efficiently. Understanding these differences helps in choosing the right role based on skills and career goals.

How much does a data processor earn?

The average salary for a data processor typically ranges from $30,000 to $45,000 per year, depending on experience, location, and industry. Entry-level positions may start lower, while experienced data processors with specialized skills or certifications can earn higher wages. Many roles also offer benefits such as health insurance and paid time off.

What do you do as a data processor?

A data processor collects, organizes, and manages data to ensure accuracy and consistency. They often use software tools like spreadsheets or databases and may perform tasks such as data entry, validation, and updating records to support business operations.
More about Data Processor jobs

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For Data Processor jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Data Processor jobs in Michigan look for?

The top searched job categories for Data Processor jobs in Michigan are:

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Cities in Michigan with the most Data Processor job openings:

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For Data Processor jobs in MI, the most frequently searched job titles are:

Data Processor jobs near you
Infographic showing various Data Processor job openings in Michigan as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 12% Part Time, 4% Contract, and 1% Nights. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $36,740 per year, or $17.7 per hour.

GCP Data Engineer with Python

Dearborn, MI • On-site

Saransh Inc
IT Services • 51 - 200 employees
Learn more about Saransh Incexternal

$105K - $126K/yr

Contractor

Re-posted 11 days ago

Job description

Role: GCP Data Engineer with Python
Location: Dearborn, MI (4 days a week onsite)
Job Type: Contract
 
Experience: Overall 8 to 12 years

Job Summary:
  • The Data Engineer will be responsible for supporting the Credit Global Securitization (GS) team’s upskilling initiative by contributing to data engineering efforts across cloud and traditional platforms.
  • This role is intended to accelerate development and delivery.
  • The engineer will work closely with cross-functional teams to build, optimize, and maintain data pipelines and workflows using GCP, Python, and ETL tools.

Required Technical Skills:
  • Minimum 3+ years of hands-on experience with Google Cloud Platform (GCP), specifically using Astronomer/Composer for orchestration.
  • Strong proficiency in Python for data engineering and automation.
  • Experience with RDBMS technologies such as DB2 and Teradata.
  • Exposure to Big Data ecosystems and distributed data processing.

Nice to have Technical Skills:
  • Prior experience with ETL tools like DataStage or Informatica.

Responsibilities:
  • The Data Engineer will play a key role in the developing and maintaining scalable data pipelines and workflows.
  • The engineer will work with GCP tools like Astronomer/Composer and leverage Python for automation and transformation tasks.
  • The role involves integrating data from RDBMS platforms such as DB2 and Teradata, and supporting ETL processes using tools like DataStage or Informatica.
  • The engineer will collaborate with existing team members, including Software Analysts and Scrum Masters, and will be expected to contribute to knowledge sharing and process improvement.
     
Specifically:
  • Develop and implement solutions using GCP, Python, Big Data technologies to enhance data analysis capabilities.
  • Collaborate with cross-functional teams to design and optimize data models in Teradata and DB2 environments.
  • Utilize Python for scripting and automation to streamline geospatial data processing tasks.
  • Integrate and manage data workflows using Cloud Composer to ensure efficient data pipeline operations.
  • Leverage GCP Cloud to deploy scalable applications and services.