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Remote Healthcare Data Engineer Jobs in Michigan

Kobie Marketing

Sr. Data Engineer

Detroit, MI · Remote

$104K - $142K/yr

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... Our Data Engineering team builds and maintains the operational data foundation that powers real ...

Ford Motor Company

Data Scientist

Dearborn, MI · Remote

Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

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All JobsHealthcare Data Engineer JobsRemote Healthcare Data Engineer JobsRemote Healthcare Data Engineer Jobs in Michigan

Remote Healthcare Data Engineer information

What is the difference between Remote Healthcare Data Engineer vs Remote Healthcare Data Analyst?

AspectRemote Healthcare Data EngineerRemote Healthcare Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; experience with data pipelinesBachelor's in Statistics, Data Analysis, or related; proficiency in data visualization
Work EnvironmentDevelops data infrastructure, manages pipelines, collaborates with engineersInterprets data, creates reports, supports decision-making
Industry UsageDesigns data systems for healthcare organizations, research institutionsAnalyzes healthcare data for insights, reporting, and compliance
Common Search/ComparisonOften compared for technical roles in healthcare data managementRelated but focuses on analysis rather than infrastructure

The main difference is that Remote Healthcare Data Engineers build and maintain data systems and pipelines, while Remote Healthcare Data Analysts interpret data and generate reports. Both roles require healthcare industry knowledge, but engineers focus on data infrastructure, whereas analysts focus on data insights.

What skills and qualifications are needed to thrive as a remote healthcare data engineer?

To thrive as a Remote Healthcare Data Engineer, you need expertise in data architecture, database management, and healthcare data standards, often supported by a degree in computer science or a related field. Familiarity with tools like SQL, Python, cloud platforms (e.g., AWS or Azure), and knowledge of healthcare-specific systems such as HL7 or FHIR is crucial. Strong problem-solving skills, attention to detail, and effective remote communication are standout soft skills in this role. These competencies ensure secure, accurate handling of sensitive health information and support effective data-driven decisions in healthcare organizations.

How does a remote healthcare data engineer collaborate with clinical and IT teams to ensure data accuracy and security?

Remote Healthcare Data Engineers frequently work cross-functionally with clinical staff, IT professionals, and data analysts to design, implement, and maintain secure data pipelines. They participate in virtual meetings to understand data requirements, clarify data definitions, and ensure compliance with healthcare regulations such as HIPAA. Collaboration tools and secure communication platforms are essential to share updates, resolve issues, and document workflows. This teamwork helps ensure that data is accurate, accessible, and protected, ultimately supporting improved patient outcomes and operational efficiency.

What does a remote healthcare data engineer do?

A Remote Healthcare Data Engineer designs, builds, and maintains data systems that collect, store, and process healthcare data, all while working from a remote location. They ensure that large volumes of medical records, patient information, and other healthcare-related data are organized and secure. Their work supports healthcare providers and researchers in making data-driven decisions, improving patient outcomes, and ensuring compliance with privacy regulations. Remote Healthcare Data Engineers often collaborate with data scientists, analysts, and IT teams to create efficient and scalable data pipelines tailored to the unique needs of healthcare organizations.
What are popular job titles related to Remote Healthcare Data Engineer jobs in Michigan? For Remote Healthcare Data Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Healthcare Data Engineer jobs in Michigan look for? The top searched job categories for Remote Healthcare Data Engineer jobs in Michigan are:
What cities in Michigan are hiring for Remote Healthcare Data Engineer jobs? Cities in Michigan with the most Remote Healthcare Data Engineer job openings:
Remote Healthcare Data Engineer jobs near you
Infographic showing various Remote Healthcare Data Engineer job openings in Michigan as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution.

Sr. Data Engineer

Kobie Marketing

Detroit, MI • Remote

$104K - $142K/yr

Full-time

Re-posted 3 days ago

Job description

Join a National Top Workplace 
 
Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We're always looking for talented individuals who are ready to join a collaborative, growth-focused culture. As a partner to some of the world's most recognized brands, we are leaders in loyalty, helping brands build lasting emotional connections with their consumers. 
 
Join Us from Anywhere 
While our headquarters are nestled in sunny St. Petersburg, Florida, Kobie embraces a flexible work environment, offering teammates the freedom to work remotely. We understand the importance of work-life balance and support our team with: 

         Flexible Time Off to recharge when needed 
         Nine Company-Wide Holidays 
         A diverse suite of benefits prioritizing your growth, development, and personal well-being 

Discover more about our perks and benefits here. 
 
Kobie is a values-led organization where we believe that everyone is a leader, regardless of their position or role. 


About the team and what we'll build together

At Kobie, we turn our client's loyalty data into actionable intelligence that drives enterprise value. Our Data Engineering team builds and maintains the operational data foundation that powers real-time dashboards, client-facing reporting, and emerging AI-driven products, serving a growing portfolio of enterprise loyalty program clients across some of the most recognized brands in the world.

As a Senior Data Engineer, you will be a key technical contributor and operational owner within our data engineering function. You will bring deep Snowflake expertise and strong engineering instincts to own production data pipelines, lead client implementations, and help us evolve our data architecture to support event-driven and AI-powered workflows, all within a multi-hundred terabyte Snowflake environment where the data problems are as complex as the brands behind them.

How you will make an impact

  • Serve as the operational backbone of Kobie's data platform, ensuring the ETL/ELT pipelines, dimensional models, and Snowflake environments that power client reporting and dashboards run reliably, at scale, every day.
  • Translate client loyalty program requirements into production-ready data warehouse structures - from source system analysis and dimensional modeling through to the KALC (Kobie Alchemy Loyalty Cloud) platform tables and extracts that downstream reporting and client services teams depend on.
  • Diagnosing and resolve data pipeline failures quickly enough that clients and internal stakeholders rarely notice they happened by bringing the debugging fluency and Snowflake depth to contain impact and prevent recurrence.
  • Build a data architecture that can absorb change by redesigning Kobie's data mart to support an incoming event-driven, domain-driven application layer without breaking the operational foundation already in production.
  • Deliver the data infrastructure that makes AI-powered loyalty products possible. Not by building the models, but by building the reliable, well-governed platform that Kobie's innovation team needs to produce them.
  • Leave every pipeline more trustworthy than you found it, through automated testing, audit logging, CI/CD discipline, and documentation that makes the platform easier for the next engineer to own.

What you need to be successful

Required

  • 6+ years of Data Engineering experience designing and operating production grade data pipelines.
  • 3+ years of hands-on Snowflake experience as a primary data warehousing solution, with deep fluency across data sharing, data clean rooms, marketplace, and Snowpark.
  • Strong proficiency in SQL, Python, and JavaScript for data transformation, pipeline development, and automation scripting.
  • Demonstrated CI/CD experience using GitHub and GitHub Actions
  • Experience with data replication tools (Kafka, GoldenGate, HVR, Qlik Replicate or similar)
  • Deep understanding of Kimball dimensional modeling: star schemas, slowly changing dimensions, snapshot and transaction fact tables.
  • Experience integrating a wide range of data sources, including APIs, messaging systems, and streaming platforms.
  • Solid grounding in OLTP, Data Vault, and data warehouse architecture patterns, with the ability to assess source systems and translate business requirements into dimensional models.
  • Experience designing event-driven architectures and understanding how they shape data pipeline design.
  • Familiarity with domain-driven design concepts and how application architecture changes flow downstream into the warehouse.
  • Cloud experience with Azure and/or AWS.
  • Comfort working independently across concurrent projects in an Agile environment, with strong communication to non-technical data stakeholders.

Strongly Preferred

  • Prior experience in a terabyte-scale, multi-client data warehouse environment, you've worked at this kind of scale before and know what it demands.
  • Experience with data replication tool Qlik Replicate, preferred
  • Familiarity with Apache NiFi or comparable data flow orchestration tools, preferred
  • Exposure to AI workflow integration within a data warehousing context, or experience building pipelines that serve downstream machine learning use cases.
Who we are  As a trusted partner, Kobie delivers market-leading, end-to-end loyalty solutions designed to enable customer experiences for the world's most successful brands. We do this with a strategy-led technology approach that uncovers the truth behind what drives consumers on an emotional level. We believe that our team's passion and expertise are the driving forces behind our success and are proud to be named a Top Workplaces in the USA, where the best and brightest in loyalty drive our mission of growing enterprise value through loyalty. 
 
A place for all We celebrate and embrace diversity at Kobie! 
Employment at Kobie is based solely on an individual's merit and qualifications, which are directly related to professional competence. We do not discriminate against any teammate or applicant because of race,color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy, or any other characteristic protected by applicable law. 
 
We are fiercely committed to fostering a workplace where teammates can bring their authentic selves to work every day. Our DEI initiatives, including various committees, ensure that principles of equity, diversity, and inclusion are deeply ingrained throughout Kobie. While our leadership team fully supports our policy of nondiscrimination and equal opportunity, it is the responsibility of all teammates to uphold these values. 
 
Ready to join us? If you're ready to make an impact and grow in a supportive, innovative environment, we'd love to hear from you. Apply today and join the best and brightest in loyalty! 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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