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Remote Data Engineering Jobs in Kalamazoo, MI (NOW HIRING)

Senior Staff Data Engineer

Portage, MI · On-site +1

$153K - $255K/yr

Remote Join a team focused on building scalable, enterprise-grade data platforms that support ... Own end-to-end delivery of complex data engineering initiatives from requirements through ...

Data Security Consultant

Three Rivers, MI · On-site +1

$130K - $150K/yr

... Engineer (CDPSE) are considered an asset. * Values matter to you. You bring your real self to work ... remote (if non-local) or hybrid work arrangement where you'll spend 2 days per week on-site in ...

Data Security Consultant

Three Rivers, MI · On-site +1

$130K - $150K/yr

... Engineer (CDPSE) are considered an asset. * Values matter to you. You bring your real self to work ... remote (if non-local) or hybrid work arrangement where you'll spend 2 days per week on-site in ...

The Product Engineering area is responsible for designing, writing, testing and deploying the code ... Python (AI/ML development & data processing) * NodeJS with TypeScript (backend services) * AWS ...

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Remote Data Engineering information

See Kalamazoo, MI salary details

$42K

$122.4K

$167.5K

How much do remote data engineering jobs pay per year?

As of Sep 9, 2026, the average yearly pay for remote data engineering in Kalamazoo, MI is $122,375.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,000.00 and $129,700.00 per year, depending on experience, location, and employer.

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?

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.

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 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 Kalamazoo, MI?

The most popular types of Data Engineering jobs in Kalamazoo, MI are:

What are popular job titles related to Remote Data Engineering jobs in Kalamazoo, MI?

For Remote Data Engineering jobs in Kalamazoo, MI, the most frequently searched job titles are:

What job categories do people searching Remote Data Engineering jobs in Kalamazoo, MI look for?

The top searched job categories for Remote Data Engineering jobs in Kalamazoo, MI are:

What cities near Kalamazoo, MI are hiring for Remote Data Engineering jobs?

Cities near Kalamazoo, MI with the most Remote Data Engineering job openings:

Infographic showing various Remote Data Engineering job openings in Kalamazoo, MI as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $122,375 per year, or $58.8 per hour.

Senior Lead Data Engineer (Remote)

Three Rivers, MI • On-site, Remote

Stryker
Medical Equipment and Supplies Manufacturing • 10K+ employees

Full-time

Re-posted 5 days ago


Stryker rating

8.2

Company rating: 8.2 out of 10

Based on 112 frontline employees who took The Breakroom Quiz

137th 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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