Data Engineer
Healthpartners RC
Bloomington, MN · Posted October 1, 2026
Just laid off? Start here: a plan for the first weeks
See every open role at Healthpartners RC
More in Minnesota job market · All Data Engineer jobs (634) · Healthcare & Hospital Systems · Data & Analytics jobs
More roles at Healthpartners RC
- Lead Clinical Laboratory Scientist · Saint Paul, MN
- Instructional Designer · Hudson, WI
- Reimbursement Policy Analyst · Bloomington, MN
- Accreditation and Regulatory Compliance Specialist · Saint Paul, MN
- Claims Production Supervisor · Bloomington, MN
- Vice President - Medical Sub-Specialties · Bloomington, MN
Similar jobs
- Data Engineer · Trane Technologies · St Paul, MN
- Senior Data Engineer - Digital Pathology (Hybrid) · Mayo Clinic · Rochester, MN
- Senior Data Engineer · Caci-Iss · Arlington, VA
- Principal Data Engineer · Elanco US · Indianapolis, IN
- Staff Data Engineer - Hybrid · Hartford Insurance Group · Hartford, CT
- Senior Specialist, Data Architect · L3HARRIS Technologies · Huntsville, AL
Where Bloomington, MN ranks
Where Bloomington, MN placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #3Cities with the most jobs that need no experience in the Great Lakes2.1% · of 50
- #4Cities with the most hybrid jobs in the Great Lakes20% · of 50
- #6Cities with the most jobs that need no experience in the Midwest2.1% · of 67
- #6Cities with the most hybrid jobs in the Midwest20% · of 67
- #8Best cities for entry-level jobs that want AI skills in the Midwest5% · of 52
- #8Best cities for entry-level jobs that want AI skills in the Great Lakes5% · of 38
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
Data & Analytics jobs · Top Data & Analytics employers · All rankings
Pay compared with the market
This listing does not state pay. Across 203 open data engineer listings that state pay, the middle half runs $116,500 to $158,500 and the median is $135,000.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
Among database architects, AI is already used for a large share of the tasks. Measured exposure for database architects: 58% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
Say which you have and which you want to build. We use it to match you to jobs like this one.
About the job
HealthPartners is hiring Data Engineers to join our growing Pharmacy Data Team. We are currently filling multiple positions and seeking individuals who thrive on solving complex data challenges, building reliable and scalable data solutions, and leveraging data to support critical business and healthcare initiatives.
We work using Agile practices and partner closely with pharmacy business partners, informatics, finance, and operational leaders to deliver incremental value through iterative delivery, continuous improvement, and shared ownership. These roles add critical engineering capacity to support a growing portfolio of pharmacy analytics initiatives.
While all roles are focused on making healthcare more affordable and accessible through the smarter use of data, each position offers a unique area of focus and the opportunity to make a meaningful impact across our organization. Explore the specific focus areas below.
Care Delivery Pharmacy Data Team:
As part of the Care Delivery Pharmacy Data Team, you will design, build, and optimize data pipelines and products that transform pharmacy, claims, pricing, cost, and reimbursement data into trusted assets for analytics and decision-making. Collaborating closely with analysts, engineers, and business partners, you will improve data quality, automation, reliability, and accessibility while applying modern data engineering practices.
Your work will support initiatives including prescribing trend analysis, 340B program optimization, reimbursement analytics, payer contracting strategies, purchasing decisions, and executive reporting. By accelerating the integration and analysis of complex pharmacy data, you will help uncover opportunities, manage costs, and support informed decision-making across the organization.
Reporting to the Senior Manager of Health Informatics, you will join a collaborative team consisting of one Senior Data Engineer and two Data Analysts.
Health Plan Pharmacy Data Team
As part of the Health Plan Pharmacy Data Team, you will help support existing and optimize future data pipelines and products that transform pharmacy, MTM and rebate data into trusted assets for analytics and decision-making. Collaborating closely with analysts, engineers, and business partners, you will improve data quality, automation, reliability, and accessibility while applying modern data engineering practices.
Reporting to the Senior Manager of Health Informatics/Data Operations, you will join a collaborative team of engineers and analysts.
Required Qualifications:
Bachelor's degree in Computer Science, Data Science, Social Science, Operations Research, Statistics, Applied Mathematics, Econometrics, or another quantitative field with four (4) years of experience in business analytics, data science, software development, data modeling, and/or data engineering, OR a Master's degree in Computer Science, Software Engineering, Mathematics, or a related field.
Two (2) years of experience in a hands-on data engineering role.
Two (2) years of experience working with SQL and Python.
Two (2) years of experience working with modern big data platforms such as: Azure Data Factory, Azure Synapse, PowerBI, Databricks, or similar.
Knowledge of data modeling concepts and techniques, including star and snowflake schemas, denormalized data models, and third normal form (3NF).
Understanding of common data formats, including Parquet, CSV, and JSON.
The following qualifications are considered critical to success in this role. Candidates should have substantial, demonstrated experience in these areas. Knowledge of data processing methodologies, including batch processing, time-based partitioning, distributed processing, and real-time data streaming.
Strong data profiling, analytical, and critical thinking skills, with the ability to identify patterns, trends, and opportunities within complex datasets.
Experience with version control and CI/CD practices; Git experience preferred.
Self-motivated, curious, and creative, with the ability to work independently and take initiative.
Strong verbal and written communication skills, with the ability to effectively partner with business stakeholders, end users, and technical teams.
Demonstrated ability to collaborate effectively within diverse, cross-functional development and operations teams.
Preferred Qualifications:
Experience working in Agile and Scrum-based development environments.
Experience working in a public cloud infrastructure.
Interest in advancing DataOps practices, including CI/CD, Infrastructure as Code (IaC), automated testing, and configuration management.
Knowledge of healthcare operations, healthcare data, and payer or care delivery processes.
Proven ability to collaborate effectively with product managers, program managers, engineers, and business stakeholders.
Strong analytical, problem-solving, and critical thinking skills.
Demonstrated ability to influence without direct authority and succeed in a fast-paced, evolving environment.
Ideal candidates will have expertise in one or more of the following areas: Relational databases, including Oracle and Microsoft SQL Server.
SQL and Oracle performance tuning, query optimization, stored procedures, and triggers.
CI/CD, continuous testing, and site reliability engineering (SRE) practices.
Microsoft Azure technologies, including Azure Data Factory, Synapse Analytics, Purview, Databricks/Spark, Power BI, and Power Apps.
Event streaming and real-time data integration tools such as Apache Kafka, Apache Flink, and Apache NiFi.
AI/ML Operations (MLOps) and the deployment, monitoring, and support of machine learning solutions.
Hours/Location:
M-F; core business hours
This position offers a flexible hybrid work environment, with most of the work performed remotely. Team members are expected to be onsite approximately 1-2 times per month for collaboration, team meetings, and other business needs. To support these periodic onsite requirements, preference will be given to local and regional candidates.
Compensation Range:
This position is available at an intermediate or senior level, depending on qualifications.
Intermediate Data Engineer – $42.15 - $63.23 hourly
Senior Data Engineer - $51.85 - $77.77 hourly Compensation is based on the level and requirements of the role. Pay within our ranges may also be determined by education, experience, knowledge, skills, location, and abilities as well as internal equity. Hired candidates may be eligible to receive additional compensation based on role (e.g., shift differential, bonus, sales incentive, productivity pay, etc.).
Responsibilities:
All team members must champion and model our values of partnership, curiosity, compassion, integrity, and excellence, and must contribute to a culture of continuous learning.
Collaborate with stakeholders, data scientists and analysts to frame problems, clean, and integrate data, and determine the best way to provision that data on demand.
Collaborate with other developers to design technology solutions that achieve measurable results at scale.
Collaborate with data scientists to train, develop, and operationalize learning models.
Build, design, and develop scalable, efficient data pipeline processes to manage data ingestion, cleansing, transformation, integration, and validation required to provide access to prepared data sets for analysts and data scientists.
Evaluate and recommend technology and frameworks for building cross product data assets to optimize for flexibility, long-term viability, and time to market.
Guide, mentor, influence, and adopt a cloud-first modern data architectural direction and consistently adopt the associated standards and best practices.
Anticipate the need for data governance and work with designated committees to ensure that data modeling and data handling procedures are compliant with applicable laws and policies across data pipeline.
Leads root cause analysis in response to detected problems/anomalies to identify the reason for alerts and implement advanced solutions that prevent recurring points of failure.
Applies in-depth knowledge of the business to design a data model that is appropriate for the project and translates business requirements into design specification documents to model the flow and storage of data across multiple data pipelines.
Identifies multiple, complex data sources and builds advanced code to extract raw data from identified upstream sources using query languages, tools, or machine learning algorithms, while assuring accuracy, validity, and reliability of the data across the pipeline.
Formulate techniques for quality data collection to ensure adequacy, accuracy, and legitimacy of data.
Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance.
Participate in code reviews and champion the adoption of best practices.
Support the data environment by releasing new features, resolving issues for users, and working with other technology teams.
Monitor and analyze information and data systems and evaluate their performance to discover ways of enhancing them (such as new technologies and upgrades).
Applies in-depth knowledge of the business to design a data model that is appropriate for the project and translates business requirements into design specification documents to model the flow and storage of data across multiple data pipelines.
Data engineers perform other duties as required, to meet team sprint goals.
At HealthPartners we believe in the power of good – good deeds and good people working together. As part of our team, you’ll find an inclusive environment that encourages new ways of thinking, celebrates differences, and recognizes hard work.
We’re a nonprofit, integrated health care organization, providing health insurance in six states and high-quality care at more than 90 locations, including hospitals and clinics in Minnesota and Wisconsin. We bring together research and education through HealthPartners Institute, training medical professionals across the region and conducting innovative research that improve lives around the world.
At HealthPartners, everyone is welcome, included and valued. We’re working together to increase diversity and inclusion in our workplace, advance health equity in care and coverage, and partner with the community as advocates for change.
Benefits Designed to Support Your Total Health As a HealthPartners colleague, we’re committed to nurturing your diverse talents, valuing your dedication, and supporting your work-life balance. We offer a comprehensive range of benefits to support every aspect of your life, including health, time off, retirement planning, and continuous learning opportunities. Our goal is to help you thrive physically, mentally, emotionally, and financially, so you can continue delivering exceptional care.
Join us in our mission to improve the health and well-being of our patients, members, and communities.
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant because of race, color, sex, age, national origin, religion, sexual orientation, gender identify, status as a veteran and basis of disability or any other federal, state or local protected class.