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Dbt Data Engineer Jobs in Minnesota (NOW HIRING)

Sr. Data Engineer, EDM

Hopkins, MN ยท On-site

$116K - $140K/yr

You will partner with data engineers, architects, analysts, and business subject-matter experts to ... Experience using dbt or comparable SQL-based transformation frameworks. * Knowledge of medallion ...

Posted today

Senior Data Engineer

Saint Paul, MN ยท On-site

$139K - $230K/yr

Travelers Data Engineering team constructs pipelines that contextualize and provide easy access to ... Hands-on experience with dbt for modular, version-controlled data transformation and integration ...

Collaborate with data engineers, architects, and data scientists to design scalable conceptual ... Experience with modern data stack technologies, including Snowflake, dbt, Apache Airflow, SQL, and ...

Collaborate with data engineers, architects, and data scientists to design scalable conceptual ... Experience with modern data stack technologies, including Snowflake, dbt, Apache Airflow, SQL, and ...

Collaborate with data engineers, architects, and data scientists to design scalable conceptual ... Experience with modern data stack technologies, including Snowflake, dbt, Apache Airflow, SQL, and ...

IT-Analytics Engineer

Brooklyn Park, MN ยท On-site

$119K - $143K/yr

The position combines hands-on data engineering with technical leadership, leveraging Snowflake, DBT, Matillion, and CI/CD best practices to develop scalable, high-performing data pipelines and ...

Showing results 21-40

Dbt Data Engineer information

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

To thrive as a Dbt Data Engineer, you need strong SQL skills, experience in data modeling, and a solid understanding of ELT/ETL pipelines, often supported by a degree in computer science or a related field. Familiarity with dbt (data build tool), version control systems like Git, and cloud data platforms such as Snowflake or BigQuery is typically required. Attention to detail, problem-solving abilities, and effective collaboration are essential soft skills for this role. These skills ensure robust, scalable, and maintainable data transformations that drive reliable analytics and business insights.

How does a dbt data engineer typically collaborate with data analysts and other stakeholders?

As a Dbt Data Engineer, you'll work closely with data analysts, business intelligence teams, and sometimes product managers to translate business requirements into reliable, well-structured data models. Collaboration often involves reviewing transformation logic, ensuring data quality, and providing documentation or training on Dbt models. You may also participate in regular stand-ups or data modeling sessions to align on priorities and address data challenges collaboratively. Effective communication skills are key, as you'll bridge the gap between raw data and actionable insights.

What is a dbt data engineer?

Dbt Data Engineers are professionals who specialize in using dbt (data build tool) to transform, test, and document data within modern data warehouses. They build and maintain data pipelines by writing SQL-based transformation scripts and ensuring data quality through automated testing. Dbt Data Engineers collaborate closely with analytics teams to create reliable, well-documented datasets that support business intelligence and analytics initiatives.

What is the difference between Dbt Data Engineer vs Data Analyst?

AspectDbt Data EngineerData Analyst
Primary FocusBuilding and maintaining data transformation pipelines using dbtAnalyzing data to generate reports and insights
Skills & ToolsSQL, dbt, ETL pipelines, cloud platformsSQL, Excel, BI tools, data visualization
Work EnvironmentData engineering teams, cloud data platformsBusiness units, reporting teams
CertificationsSQL, cloud certifications, dbt trainingData analysis, visualization certifications

While both roles work with data and SQL, Dbt Data Engineers focus on developing scalable data transformation pipelines using dbt, whereas Data Analysts primarily analyze data to produce reports and insights. The roles complement each other within data teams but differ in technical scope and responsibilities.

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

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

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

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

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

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

Infographic showing various Dbt Data Engineer job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 9% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Sr. Data Engineer, EDM

Medica Services Company LLC

Hopkins, MN โ€ข On-site

$116K - $140K/yr

Full-time

Posted 22 hours ago

Posted today


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 — 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 Medica’s Snowflake platform and lead its progression from raw Bronze-layer structures into standardized Silver-layer models aligned with Medica’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 Medica’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. Medica’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.