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Remote Data Quality Reviewer Jobs in Michigan (NOW HIRING)

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

... ensure data quality and analytical integrity. * Designing and deploying lightweight internal ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

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Remote Data Quality Reviewer information

What is a remote data quality reviewer?

A Remote Data Quality Reviewer is a professional who evaluates and ensures the accuracy, completeness, and reliability of data collected or processed by an organization, all while working from a remote location. Their duties often include checking data for errors, inconsistencies, or missing information, and recommending corrections or improvements. They may work with various types of data, such as customer records, survey responses, or financial information, depending on the industry. This role is crucial for maintaining high data standards and supporting decision-making processes within a company.

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

To thrive as a Remote Data Quality Reviewer, you generally need strong analytical abilities, attention to detail, and experience with data validation, often supported by a bachelor's degree in a relevant field such as statistics, computer science, or information management. Familiarity with data management tools, spreadsheet software (like Excel), and database systems, as well as knowledge of quality assurance frameworks, is typically required. Excellent written communication, critical thinking, and the ability to work independently are important soft skills for this remote position. These capabilities ensure accurate data assessment, help maintain data integrity, and contribute to reliable decision-making across organizations.

What are some common challenges faced by remote data quality reviewers, and how can they be addressed?

Remote Data Quality Reviewers often encounter challenges such as managing large data sets, maintaining focus during repetitive review tasks, and ensuring effective communication with distributed teams. Staying organized with clear workflow tools and setting regular check-ins with team members can help mitigate feelings of isolation and prevent errors. Additionally, leveraging automated validation tools and maintaining up-to-date documentation ensures consistency and accuracy in data review processes.

What are popular job titles related to Remote Data Quality Reviewer jobs in Michigan?

For Remote Data Quality Reviewer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Data Quality Reviewer jobs in Michigan look for?

The top searched job categories for Remote Data Quality Reviewer jobs in Michigan are:

What cities in Michigan are hiring for Remote Data Quality Reviewer jobs?

Cities in Michigan with the most Remote Data Quality Reviewer job openings:

Remote Data Quality Reviewer jobs near you
Infographic showing various Remote Data Quality Reviewer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, 4% Contract, and 1% Nights. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution.

Senior Lead Data Engineer (Remote)

Stryker

Three Rivers, MI • On-site, Remote

Full-time

Re-posted 2 days ago

Stryker rating

8.2

Company rating: 8.2 out of 10

Based on 112 frontline employees who took The Breakroom Quiz

134th of 499 rated machine equipment manufacturers

Job description

Work Flexibility: Remote

As a Senior Lead, Data Engineering, you will serve as a technical leader who helps shape the future of enterprise data solutions. In this role, you will drive complex data initiatives, influence technical strategy, and partner with teams across the organization to build scalable, high-impact data products. This is an opportunity to solve challenging business problems while mentoring fellow engineers and elevating data engineering best practices.

What You Will Do

  • Lead the architecture, development, and modernization of scalable enterprise data platforms that support global procurement analytics and business transformation.
  • Define and help execute a multi-year data engineering strategy focused on platform scalability, reliability, automation, technical debt reduction, and long-term maintainability.
  • Design, build, and optimize Azure-based data solutions using technologies such as Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation.
  • Integrate and harmonize data across multiple ERP systems by standardizing supplier, purchasing, and master data into common enterprise data models.
  • Partner with procurement analysts, architects, engineers, and business stakeholders to translate complex business needs into reusable, scalable data products and engineering solutions.
  • Establish engineering standards, conduct architecture reviews, improve documentation, and mentor engineers to raise the overall technical capability of the team.
  • Identify and implement AI-enabled approaches that accelerate development, improve data quality, automate documentation, support testing, and enhance analyst productivity.
  • Evaluate and recommend tools, frameworks, patterns, and platform investments that improve performance, reliability, security, governance, and operational efficiency.
  • Support the development of internal data products, APIs, and user-facing applications that simplify access to procurement insights and improve analyst productivity.
  • Present technical recommendations, roadmap priorities, tradeoffs, and business impacts to technical and non-technical stakeholders, including leadership teams.

What you need

Required

  • Bachelor's degree in Computer Science, Data Engineering, Data Science, Information Systems, Mathematics, Statistics, or a related technical field.
  • 6+ years of experience in data engineering, analytics engineering, software engineering, or enterprise data platform development.
  • Proven experience architecting, building, and modernizing scalable cloud-based data platforms in an enterprise environment.
  • Hands-on experience with Azure-based data engineering technologies, including Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation.
  • Strong proficiency in SQL and Python, with experience using Spark or similar distributed data processing frameworks.
  • Experience designing reliable ETL/ELT pipelines, data warehouse or Lakehouse architectures, data models, and performance-optimized analytics solutions.
  • Experience integrating data from multiple ERP or enterprise source systems and harmonizing inconsistent master, supplier, purchasing, or transactional data into common data models.
  • Experience with API integrations, REST services, authentication, security, data governance, and production support practices.
  • Demonstrated ability to establish engineering standards, conduct architecture reviews, improve documentation, mentor engineers, and influence technical direction without direct authority.
  • Ability to partner with analysts, engineers, architects, and business stakeholders to translate complex business requirements into scalable, maintainable engineering solutions.

Preferred

  • Master's degree in Computer Science, Data Engineering, Data Science, Information Systems, Business Analytics, or a related technical field.
  • Experience supporting procurement, supply chain, manufacturing, finance, or ERP analytics in a global enterprise environment.
  • Experience building or modernizing enterprise data platforms, Lakehouse architectures, or cloud analytics ecosystems at scale.
  • Hands-on experience with multiple ERP platforms, such as SAP ECC, SAP S/4HANA, Oracle, JD Edwards, Infor, QAD, or Microsoft Dynamics.
  • Full-stack engineering experience, including React, Next.js, Vercel, API development, authentication, and internal web application development.
  • Experience using AI-assisted engineering tools and workflows, such as GitHub Copilot, ChatGPT, Claude, Cursor, AI coding agents, AI-assisted testing, or AI-assisted documentation.
  • Experience designing internal tools, data products, APIs, or analyst-facing applications that improve productivity and simplify access to insights.
  • Experience leading cloud modernization, platform migration, technical debt reduction, automation, or data quality improvement initiatives.
  • Experience with Power BI, Tableau, or similar business intelligence and visualization tools.
  • Demonstrated curiosity and continuous learning mindset, with a track record of experimenting with emerging technologies and applying them to practical engineering or analytics use cases.

United States of America Pay Ranges:

  • USN: $118,000 - $196,700 USD Annual
  • US5: $123,900 - $206,500 USD Annual
  • US10: $129,800 - $216,400 USD Annual
  • US15: $135,700 - $226,200 USD Annual
  • US20: $141,600 - $236,000 USD Annual
  • US30: $153,400 - $255,700 USD Annual
View the U.S. work location and transparency guide to find the pay range for your location.

Travel Percentage: 10%Stryker Corporation is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, gender identity, sexual orientation, national origin, disability, or protected veteran status. Stryker is an EO employer - M/F/Veteran/Disability.Stryker Corporation will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.

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