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Junior Data Engineering Jobs in Minnesota (NOW HIRING)

Data Engineer with AI/ML

Minnetonka, MN · On-site +1

$72K - $130K/yr

We are seeking a highly skilled and motivated Data Engineering Analyst with AI/ML expertise to ... Mentor junior engineers and foster knowledge-sharing within the team * Work independently to ...

You'''''ll partner closely with data engineers, business stakeholders, and fellow data scientists ... Mentor junior and mid-level Data Scientists through technical guidance, code reviews, and ...

This includes procurement of product documentation, managing data integrity in the Quality Module, and performing lab tests and production support. The Junior Technical Services Engineer also manages ...

Showing results 21-40

Junior Data Engineering information

See Minnesota salary details

$32.8K

$70.3K

$107.2K

How much do junior data engineering jobs pay per year?

As of Aug 20, 2026, the average yearly pay for junior data engineering in Minnesota is $70,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,500.00 and $78,400.00 per year, depending on experience, location, and employer.

What does a junior data engineer do?

A Junior Data Engineer typically assists in designing, building, and maintaining data pipelines and databases to support analytics and business needs. They work with large datasets, ensuring data is collected, stored, and processed efficiently and accurately. Responsibilities often include data cleaning, ETL (Extract, Transform, Load) processes, and collaborating with data analysts and other engineers. Junior Data Engineers are usually early in their careers and work under the guidance of more experienced data engineers while developing their technical and problem-solving skills.

What are the key skills and qualifications needed to thrive as a junior data engineer?

To thrive as a Junior Data Engineer, you need a solid understanding of data structures, SQL, and programming languages like Python or Java, often supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms (such as AWS or Azure), and data warehousing solutions is typically required. Strong problem-solving abilities, attention to detail, and effective communication help you excel in team environments and manage complex data workflows. These skills ensure you can reliably build, maintain, and optimize data pipelines that support organizational decision-making.

What are some typical challenges a junior data engineer may face when starting out, and how can they overcome them?

As a Junior Data Engineer, one common challenge is adapting to complex data infrastructure and unfamiliar tools or frameworks. You may also find it challenging to ensure data quality and consistency while working with large datasets. Collaborating closely with senior engineers and asking questions is key to overcoming these hurdles. Taking advantage of onboarding resources, documentation, and code reviews will help you learn best practices and improve your skills quickly. Embracing continuous learning and seeking feedback will set you up for long-term growth in data engineering.

What is the difference between Junior Data Engineering vs Data Analyst?

AspectJunior Data EngineeringData Analyst
Required SkillsBasic SQL, Python, data pipeline knowledgeData visualization, SQL, Excel
CertificationsEntry-level certifications in data engineering or related fieldsCertifications in data analysis or visualization tools
Work EnvironmentData engineering teams, IT departmentsBusiness units, marketing, finance teams
Industry UsageBuilding and maintaining data pipelines and infrastructureInterpreting data, creating reports and dashboards

Junior Data Engineering focuses on developing and maintaining data pipelines and infrastructure, requiring skills in SQL and Python. Data Analysts interpret data and create reports, often using visualization tools. While both roles work with data, Junior Data Engineers handle data flow and storage, whereas Data Analysts focus on data interpretation and insights.

What are the most commonly searched types of Data Engineering jobs in Minnesota?

The most popular types of Data Engineering jobs in Minnesota are:

What are popular job titles related to Junior Data Engineering jobs in Minnesota?

For Junior Data Engineering jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Junior Data Engineering jobs in Minnesota look for?

The top searched job categories for Junior Data Engineering jobs in Minnesota are:

What cities in Minnesota are hiring for Junior Data Engineering jobs?

Cities in Minnesota with the most Junior Data Engineering job openings:

Infographic showing various Junior Data Engineering job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $70,321 per year, or $33.8 per hour.

Senior Cloud Data Engineer - Remote

UnitedHealth Group

Eden Prairie, MN • On-site, Remote

$106K - $146K/yr

Full-time

Retirement

Posted 8 days ago


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

190th of 889 rated healthcare providers


Job description

Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us to start Caring. Connecting. Growing together.
Optum Advisory Services operates on the intersection of strategy, business operations, data and technology to help our clients realize exceptional business value. We harness data and technology and use them to reimagine business transformations to design and architect solutions that help realize exceptional value for our clients. We are uniquely positioned to accelerate the value proposition for our clients across the healthcare ecosystem with our unwavering focus on making health system work better for everyone.
The Senior Cloud Data Engineer will be a key technical resource during the solution implementation of cloud-centric data management architecture. The primary role of the Senior Cloud Data Engineer is to take the design and technical specifications and develop effective and high-quality technical solutions that meet business requirements. The technical domain of the Cloud Data Engineer includes understanding Data Acquisition/Integration (DA/DI) best practices, tools and technologies, security in the environment, understanding of different data warehousing and dimensional modelling concepts, DI development, performance tuning and support system testing.
We are seeking an experienced Senior Cloud Data Engineer to support large-scale Cloud Data Modernization initiatives. The successful candidate will lead the migration and modernization of legacy data platforms, ETL/ELT processes, and enterprise data warehouses to cloud-native solutions leveraging Azure, Snowflake, Databricks, and modern data engineering practices. This role combines hands-on engineering, technical leadership, and solution implementation responsibilities to deliver scalable, secure, high-quality cloud data platforms that support analytics, reporting, and operational workloads.
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Primary Responsibilities:
Cloud Data Modernization
  • Provide technical leadership in design and engineering for the modernization of legacy data platforms, ETL/ELT processes, and enterprise data warehouses to new technologies in the Public Cloud (AWS/Azure)
  • Review and analyze existing SSIS, SQL Server, and legacy ETL implementations and develop modernization strategies
  • Design, develop, and implement cloud-native data solutions utilizing Azure Data Factory (ADF), Azure Data Lake Storage Gen2 (ADLS Gen2), Snowflake, Databricks, Azure cloud services

Data Engineering & Integration
  • Design and develop scalable ETL/ELT pipelines supporting batch and streaming workloads
  • Create source-to-target mappings and implement data ingestion frameworks supporting structured and unstructured data
  • Build and optimize cloud data warehouses, data marts, and lakehouse architectures
  • Implement full and incremental load patterns, change data capture (CDC), and automated data validation processes
  • Perform data profiling, data quality assessment, and root cause analysis for data issues
  • Create Process Flows using diagraming tools like Visio
  • Automate pipeline processes using scheduling tools like AirFlow
  • Conduct ETL/ELT unit testing; participate in system and integration testing; identify and remedy solution defects

Data Architecture & Modeling
  • Design and implement enterprise data warehouse solutions utilizing dimensional modeling concepts including Star schemas, Snowflake schemas, Fact and dimension design, Data pipeline architectures
  • Collaborate with business and technical stakeholders to understand requirements and translate them into scalable solutions

Cloud Security & Governance
  • Implement appropriate data security, privacy, governance, and compliance controls
  • Ensure compliance with organizational standards for data protection, auditability, and data quality
  • Establish data lineage, monitoring, and operational support processes

DevOps & Delivery
  • Implement CI/CD pipelines and DevOps practices using GitHub Actions and other modern delivery tools
  • Support Agile software delivery practices and contribute across the full development lifecycle, including: Requirements, Design, Development, Testing, Deployment, Production support

Leadership & Collaboration
  • Provide technical leadership for cloud data engineering initiatives
  • Mentor junior engineers and contribute to engineering best practices
  • Collaborate effectively in matrixed environments with business stakeholders, architects, analysts, developers, and project teams
  • Proactively identify implementation risks, constraints, and improvement opportunities
  • Self-driven, ownership mindset to navigate ambiguity, identify options to resolve constraints, mitigate implementation risks and define solutions to implementation challenges with minimal supervision
  • Build partnership and rapport with client technical resources by demonstrating solid written and verbal communication, presentation, analytical and interpersonal skills
  • Ability to work closely with Business Analysts and SMEs to understand business requirements
  • Ability to work in a matrixed team environment with distributed responsibility across different teams
  • Proactive and diligent in identifying and communicating scope, design, development issues and recommending potential solutions

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.
Required Qualifications:
  • 5+ years of experience in designing, developing, and implementing enterprise data warehouse and analytics solutions on prem and on cloud
  • 3+ years of hands-on cloud data engineering experience utilizing Azure cloud technologies
  • 3+ years of experience working as part of data engineering teams, including offshore teams, through a product life cycle - requirements, design, development, testing and deployment
  • Hands-on experience with AI-enabled data engineering tools such as Databricks Genie, GitHub Copilot, Snowflake Cortex, LLMs, prompt engineering
  • Experience designing and implementing healthcare data and analytics solutions, including large-scale cloud data modernization, data warehouse migration, and platform transformation initiatives
  • Experience implementing CI/CD and DevOps practices using GitHub and GitHub Actions
  • Experience working within Agile delivery methodologies
  • Solid experience with Azure Data Factory (ADF), Databricks, Snowflake, ADLS Gen2, SQL Server, Python, Spark/Pyspark, ETL/ELT development
  • Solid understanding of data warehousing concepts, dimensional modeling, data quality management, data governance, data pipeline architecture
  • Comprehensive understanding of healthcare payer operations, CMS and NCQA regulatory frameworks, Population Health Management, Healthcare Economics, and FACETS-supported business processes across Claims, Membership, Eligibility, Provider, and Care Management domains
  • Proven expertise in managing highly sensitive PHI/PII, claims, provider, clinical, and member data while supporting Risk Adjustment (HCC/RAF), quality measurement programs, and ensuring HIPAA compliance, data governance, privacy, and security standards
  • Solid expertise in healthcare interoperability and industry standards, including HL7, FHIR, X12 EDI (837/835/834), ICD-10, CPT, HCPCS, and LOINC
  • Demonstrated ability to meet tight deadlines, follow development standards and effectively raise critical issues with the client
  • Demonstrated ability to work independently, manage ambiguity, and deliver high-quality solutions
  • Proven excellent analytical, problem-solving, communication, and stakeholder management skills
  • Proven ability to partner with AI Engineering on RAG pipelines, embedding strategies, and vector stores that ground responses in EHR data, clinical documentation, and medical literature, including implementing data refresh patterns that sync with EHR updates and evidence-based guideline revisions
  • Ability to travel 10 - 20% when required

Preferred Qualifications:
  • Snowflake, Azure, Databricks, or Cloud Data Engineering certification
  • Experience with cloud data platforms across Azure, AWS, and/or Google Cloud
  • Experience working with healthcare claims, member, enrollment, or clinical data
  • Experience with streaming and event-driven architecture utilizing Kafka and Spark Structure Streaming
  • Experience with Infrastructure as Code (Terraform) and container technologies (Docker, Kubernetes)
  • Architected HIPAA-compliant Azure and Snowflake-based healthcare analytics platforms integrating Claims, Membership, Provider, Clinical, Laboratory, Pharmacy, and Care Management data

*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 - $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.
UnitedHealth Group is a drug-free workplace. Candidates are required to pass a drug test before beginning employment.

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