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Insurance Data Engineer Jobs in Minnesota (NOW HIRING)

Sr. Data Engineer, EDM

Minnetonka, MN ยท On-site

$116K - $140K/yr

Experience working with healthcare payer or health insurance data. * Knowledge of healthcare ... Experience mentoring engineers or serving as a technical lead while remaining hands-on. What ...

Data Engineer

Chisago City, MN ยท On-site

$103K - $124K/yr

Supplemental insurance options * 401(k) with company match * Paid Time Off (PTO) * Paid holidays * Online apparel store Job Summary The Data Engineer builds and maintains the data layer of Kendall ...

Data Engineer

Minneapolis, MN ยท On-site

$120K - $140K/yr

We are adding Data Engineers to influence the direction of data modernization for our customers. We ... vision insurance benefits, paid time off, paid holidays, short and long-term disability, life ...

Data Engineer

Minneapolis, MN ยท On-site +1

$120K - $140K/yr

We are adding Data Engineers to influence the direction of data modernization for our customers. We ... vision insurance benefits, paid time off, paid holidays, short and long-term disability, life ...

Sr. Data Engineer

Edina, MN ยท On-site

$125K - $165K/yr

Palomar is a rapidly growing and innovative insurer focused on providing specialty insurance to ... As a Senior Data Engineer at Palomar, you will lead the design, development, and optimization of ...

Data Engineer III

Plymouth, MN ยท On-site

$119K - $143K/yr

Data Engineer III - Plymouth, MN - Onsite Daikin Applied is seeking a Data Engineer III who will be ... Multiple medical insurance plan options + dental and vision insurance * 401K retirement plan with ...

The Data Engineer will be responsible for a wide variety of tasks which include all aspects of the ... Life / Disability Insurance * 401(k) with company matching * Generous Vacation / Paid Time Off ...

Data Engineer III - Plymouth, MN - Onsite Daikin Applied is seeking a Data Engineer III who will be ... Multiple medical insurance plan options + dental and vision insurance * 401K retirement plan with ...

Senior Data Engineer

Minneapolis, MN ยท On-site

$110K - $150K/yr

Airflow, Dagster, or other orchestration tools * Healthcare or Health Insurance domain experience (Claims, Provider, Clinical, Payer) Ideal Candidate * Senior-level hands-on Data Engineer * Strong ...

Principal Data Engineer - Hybrid

Eagan, MN ยท On-site

$95.60 - $105.60/hr

Genesis10 is currently seeking a Principal Data Engineer - Hybrid position with a Regional Health Insurance Provider located in Eagan, MN. This is a 6+ month contract-to-hire opportunity.

Data Engineer (On-Premise)

Minneapolis, MN ยท On-site

$95K - $118K/yr

Ziegler CAT has an opening for a Data Engineer to design, develop, maintain, and optimize Ziegler ... Health, Dental, Vision and Life Insurance * 15 days of PTO your first year, accrual starts day 1 * ...

Data Engineer (On-Premise)

Bloomington, MN ยท On-site

$95K - $118K/yr

Ziegler CAT has an opening for a Data Engineer to design, develop, maintain, and optimize Ziegler ... Health, Dental, Vision and Life Insurance * 15 days of PTO your first year, accrual starts day 1 * ...

... insurance and more, to help you and your family take care of your whole selves.Other benefits for ... As a Lead Data Engineer, you will serve as the technical lead for the engineering team, designing ...

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Showing results 1-20

Insurance Data Engineer information

What is an insurance data engineer?

Insurance Data Engineers are professionals who design, build, and maintain data systems that support the needs of insurance companies. They are responsible for collecting, organizing, and processing large amounts of data from various sources to enable accurate risk assessment, pricing, claims analysis, and regulatory compliance. Their work helps insurers make data-driven decisions, improve efficiency, and enhance customer experiences by leveraging modern data technologies.

What are the key skills and qualifications needed to thrive as an insurance data engineer, and why are they important?

To thrive as an Insurance Data Engineer, you need strong expertise in data modeling, ETL processes, and a solid understanding of insurance data structures, typically supported by a degree in computer science, data engineering, or a related field. Proficiency with SQL, Python, big data platforms (like Hadoop or Spark), and experience with cloud data solutions such as AWS or Azure are commonly required, along with certifications like AWS Certified Data Analytics or Google Cloud Data Engineer. Excellent problem-solving, communication, and collaboration skills help you bridge technical and business needs while ensuring data quality. These abilities are essential for building robust data pipelines and enabling accurate data-driven decision making within insurance organizations.

How does an insurance data engineer typically collaborate with actuarial and underwriting teams?

Insurance Data Engineers work closely with actuarial and underwriting teams to ensure that the data infrastructure supports accurate risk assessment and pricing models. They often translate business requirements from these teams into technical specifications, build data pipelines to source and clean relevant data, and assist in implementing predictive analytics tools. Regular communication and collaboration are essential, as data engineers help bridge the gap between raw data and actionable insights for decision-making. This teamwork not only streamlines workflow but also enables continuous improvement of insurance products and customer experience.

What is the difference between Insurance Data Engineer vs Data Analyst in the insurance industry?

AspectInsurance Data EngineerData Analyst
Required CredentialsBachelor's in Computer Science, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentDevelops data pipelines, manages databases, works with big data toolsInterprets data, creates reports, visualizes insights
Employer & Industry UsageInsurance companies, tech firms in insuranceInsurance firms, consulting agencies, analytics companies

Insurance Data Engineers focus on building and maintaining data infrastructure, while Data Analysts interpret data to provide insights. Both roles are essential in the insurance industry but serve different functions in data management and analysis.

What are popular job titles related to Insurance Data Engineer jobs in Minnesota?

For Insurance Data Engineer jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Insurance Data Engineer jobs in Minnesota look for?

The top searched job categories for Insurance Data Engineer jobs in Minnesota are:

What cities in Minnesota are hiring for Insurance Data Engineer jobs?

Cities in Minnesota with the most Insurance Data Engineer job openings:

Sr. Data Engineer, EDM

Minnetonka, MN โ€ข On-site

$116K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post hasย expired today.ย Applications are no longer accepted.


Job description

Medica is a nonprofit health plan with more than a million members that serves communities in Minnesota, Nebraska, Wisconsin, Missouri, and beyond. We deliver personalized health care experiences and partner closely with providers to ensure members are genuinely cared for.

We're a team that owns our work with accountability, makes data-driven decisions, embraces continuous learning, and celebrates collaboration โ€” because success is a team sport. It's our mission to be there in the moments that matter most for our members and employees. Join us in creating a community of connected care, where coordinated, quality service is the norm and every member feels valued.

Role Summary

In this role, you will work with healthcare data ingested into Medicaโ€™s Snowflake platform and lead its progression from raw Bronze-layer structures into standardized Silver-layer models aligned with Medicaโ€™s Common Information Model (CIM). You will partner with data engineers, architects, analysts, and business subject-matter experts to interpret source data, document business rules, resolve data-quality issues, and make high-value information available across the organization.

The ideal candidate combines strong data engineering skills with a practical understanding of healthcare data and business processes. Experience with claims, membership, enrollment, providers, billing, care management, or related health plan subject areas is especially valuable.

Key Accountabilities

  • Design, develop, test, and support scalable data pipelines and transformations within Snowflake.
  • Standardize raw source data into well-defined Silver-layer data models aligned with Medicaโ€™s CIM standards.
  • Analyze complex source data, relationships, business rules, and processing behavior.
  • Translate healthcare data knowledge into durable transformation logic, documentation, and data-quality controls.
  • Develop and maintain reusable data models that support analytics, reporting, operational workflows, and downstream applications.
  • Profile data and identify quality problems, unexpected patterns, missing relationships, and discrepancies between source systems.
  • Work with subject-matter experts to validate data meaning, transformation rules, and expected outcomes.
  • Establish automated reconciliation, validation, observability, and testing practices.
  • Investigate production issues and resolve defects across ingestion, transformation, and consumption layers.
  • Contribute to data architecture, modeling, engineering standards, design reviews, and technical decision-making.
  • Provide technical guidance to other engineers and help improve team engineering practices.
  • Document data lineage, definitions, transformation logic, dependencies, and operational procedures.
  • Collaborate across engineering, architecture, analytics, governance, and business teams.

Required Qualifications

  • Bachelor's degree or equivalent experience in related field
  • 7+ years of work experience beyond degree
  • Significant professional experience in software engineering, data engineering, data integration, data warehousing, or a related discipline.
  • Advanced SQL skills and experience working with large, complex datasets.
  • Experience designing and implementing ETL or ELT pipelines.
  • Experience with dimensional, relational, or enterprise data modeling.

Skills and Attributes

  • Ability to interpret unfamiliar source data and convert it into standardized, business-meaningful models.
  • Experience implementing data-quality checks, reconciliation processes, automated tests, and production monitoring.
  • Strong troubleshooting skills across interconnected data pipelines and systems.
  • Ability to communicate effectively with both technical and nontechnical partners.
  • Demonstrated ability to work independently, manage ambiguity, and lead complex technical work.
  • Strong analytical thinking and attention to detail.
  • Curiosity about how data is created, processed, and used.
  • Ability to distinguish source-system behavior from enduring business meaning.
  • Comfort working across technical and business domains.
  • Pragmatic approach to balancing delivery, maintainability, and data quality.
  • Strong ownership mindset and commitment to reliable production outcomes.

Preferred Qualifications

  • Experience with Snowflake and cloud-based data platforms.
  • Experience using dbt or comparable SQL-based transformation frameworks.
  • Knowledge of medallion architecture, including Bronze, Silver, and Gold data layers.
  • Experience with Python, orchestration platforms, source control, automated deployment, and CI/CD practices.
  • Experience working with healthcare payer or health insurance data.
  • Knowledge of healthcare subject areas such as claims and encounters; membership and enrollment; providers and provider networks; benefits, products, and billing; care management and clinical programs; eligibility and accumulators; or electronic data interchange.
  • Experience interpreting data from healthcare administration or core processing platforms.
  • Familiarity with healthcare data governance, privacy, security, and regulatory expectations.
  • Experience developing canonical, common-information, or enterprise data models.
  • Experience mentoring engineers or serving as a technical lead while remaining hands-on.

What Success Looks Like

  • Complex source data is transformed into understandable, documented, and reusable data products.
  • Silver-layer models accurately represent healthcare concepts and business rules.
  • Data consumers can confidently find, understand, and use standardized data.
  • Data-quality issues are detected early and resolved systematically.
  • Transformation logic is tested, observable, maintainable, and traceable to its sources.
  • The broader engineering team benefits from stronger standards, documentation, and technical leadership.

This position is an Office role, which requires an employee to work onsite at our Minnetonka, MN office, on average, 3 days per week.

The full salary grade for this position is $100,300 - $172,000. While the full salary grade is provided, the typical hiring salary range for this role is expected to be between $100,300 - $150,465. Annual salary range placement will depend on a variety of factors including, but not limited to, education, work experience, applicable certifications and/or licensure, the position's scope and responsibility, internal pay equity and external market salary data. In addition to base compensation, this position may be eligible for incentive plan compensation in addition to base salary. Medica offers a generous total rewards package that includes competitive medical, dental, vision, PTO, Holidays, paid volunteer time off, 401K contributions, caregiver services and many other benefits to support our employees.

The compensation and benefits information is provided as of the date of this posting. Medicaโ€™s compensation and benefits are subject to change at any time, with or without notice, subject to applicable law.

We are an Equal Opportunity employer, where all qualified candidates receive consideration for employment indiscriminate of race, religion, ethnicity, national origin, citizenship, gender, gender identity, sexual orientation, age, veteran status, disability, genetic information, or any other protected characteristic.