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Sr Data Engineer Jobs in Rochester, MN (NOW HIRING)

Quality Engineer I

Rochester, MN · On-site

$73K - $94K/yr

... contract data item descriptions and requirements and assist with establishing the necessary ... senior engineers. • Ensures that records/files are initiated and maintained in all relevant ...

Be a senior Individual contributor of the Software Engineering teams. Be part of Technical Review ... Facilitate and drive communication between front-end, back-end, data and platform engineers. Play a ...

Mechanical Designer/Engineer

Rochester, MN · On-site

$74K - $100K/yr

This role is perfect for someone interested in mentoring our junior staff and move into Senior ... Our specialized experience includes design for data centers, healthcare, science and technology ...

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Showing results 1-20

Sr Data Engineer information

See Rochester, MN salary details

$82.3K

$128.4K

$177.9K

How much do sr data engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for sr data engineer in Rochester, MN is $128,412.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,700.00 and $146,400.00 per year, depending on experience, location, and employer.

What is the difference between Sr Data Engineer vs Data Engineer?

AspectSr Data EngineerData Engineer
Required CredentialsBachelor's degree in CS or related field; 3+ years experience; SQL, Python, SparkBachelor's degree in CS or related field; 1-3 years experience; SQL, Python, Spark
Work EnvironmentCollaborates with data scientists, analysts; designs scalable data pipelinesBuilds and maintains data pipelines; supports data analysis
Employer & Industry UsageTech companies, finance, healthcare; used for complex data projectsStartups, enterprises; used for data collection and processing

The main difference between a Sr Data Engineer and a Data Engineer lies in experience level, responsibilities, and complexity of projects. Sr Data Engineers typically have more experience, handle more complex data architecture, and mentor junior staff, whereas Data Engineers focus on building and maintaining data pipelines. Both roles are essential in data-driven organizations, but the senior role involves greater technical leadership and strategic planning.

What are the key skills and qualifications needed to thrive as a Sr Data Engineer, and why are they important?

To thrive as a Sr Data Engineer, you need expertise in data architecture, ETL processes, programming (such as Python or Scala), and a strong background in computer science or a related field. Familiarity with big data technologies like Hadoop, Spark, cloud platforms (AWS, Azure, GCP), and database management systems, along with relevant certifications, is typically required. Advanced problem-solving abilities, attention to detail, and strong collaboration skills help set top performers apart in this role. These skills and qualities ensure the efficient design, implementation, and maintenance of robust data pipelines that enable data-driven decision-making across the organization.

How do Sr Data Engineers typically collaborate with data scientists and analysts within a project team?

Sr Data Engineers play a crucial role in bridging the gap between raw data and actionable insights. They work closely with data scientists and analysts to understand data requirements, design robust data pipelines, and ensure the reliability and scalability of data infrastructure. Regular collaboration involves translating analytical needs into technical specifications, optimizing data flow, and troubleshooting data issues. This teamwork ensures that data-driven projects progress smoothly and that the analytical team has timely access to clean, well-structured data.

What are Sr Data Engineers?

Sr Data Engineers, or Senior Data Engineers, are experienced professionals responsible for designing, building, and maintaining scalable data pipelines and architectures. They work with large datasets, ensuring data quality, reliability, and accessibility for analytics and business intelligence purposes. Sr Data Engineers collaborate with data scientists, analysts, and other stakeholders to implement data solutions that support decision-making and business growth. Their expertise often includes proficiency in programming languages like Python or Java, experience with big data tools such as Hadoop or Spark, and a deep understanding of database systems.
What job categories do people searching Sr Data Engineer jobs in Rochester, MN look for? The top searched job categories for Sr Data Engineer jobs in Rochester, MN are:
What cities near Rochester, MN are hiring for Sr Data Engineer jobs? Cities near Rochester, MN with the most Sr Data Engineer job openings:
Infographic showing various Sr Data Engineer job openings in Rochester, MN as of May 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution, with an average salary of $128,412 per year, or $61.7 per hour.
Data Scientist - Research Sovereign AI

Data Scientist - Research Sovereign AI

Mayo Clinic

Rochester, MN

Full-time

Medical, Dental, Vision, Retirement

Posted 10 days ago


Mayo Clinic rating

7.8

Company rating: 7.8 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

132nd of 869 rated healthcare providers


Job description

Data Scientist Foundational Model Science

Position Summary

The Data Scientist for Foundational Model Science is the senior technical leader, and the lead scientist responsible for designing, training, and governing Mayo's multimodal foundational model. This model forms the core intelligence layer used by clinical departments, researchers, agentic workflows, and sovereign AI collaborations. The individual will work as a hands-on architect, model-builder, and researcher while acting as a player-coach, guiding strategy and building a future team.

Key Responsibilities

Scientific & Technical Leadership

  • Design multimodal foundational model architectures integrating signals from imaging, text, waveforms, structured data, graph representations, and temporal embeddings.
  • Develop fusion, alignment, and cross-modal reasoning mechanisms (early fusion, late fusion, token-level fusion, hybrid models).
  • Define and implement methods for grounded clinical reasoning, retrieval-augmented inference, graph-augmented attention, and chain-of-thought verification.
  • Establish protocols for model lifecycle governance, safe update cycles, drift-aware re-training, and provenance tracking.

Hands-On Modeling & Training

  • Train large-scale deep learning models, including multimodal architectures and domain-specific transformer-based systems, on real clinical datasets.
  • Fine-tune and adapt large language models (LLMs) for clinical reasoning, summarization, question answering, agentic behavior, and instruction-following tasks.
  • Build retrieval-augmented pipelines using embeddings, vector stores, graph traversal, and clinically grounded context construction.
  • Develop evaluation methods for reasoning quality, temporal prediction accuracy, multimodal synergy, ablation-based robustness, and counterfactual behavior.
  • Create reference-grounded training datasets, structured reasoning tasks, and multimodal benchmarks to evaluate model performance.
  • Conduct hands-on experimentation with optimization strategies, large-scale distributed training, model quantization, and inference acceleration.
  • Implement uncertainty modeling, selective prediction, abstention mechanisms, and clinically meaningful risk thresholds.
  • Build interpretable reasoning pathways, cross-modal attribution maps, and reference-grounded explanations.

Cross-functional Collaboration

  • Work closely with the Representation team to ensure representation-model alignment.
  • Partner with clinical SMEs to encode domain reasoning into reinforcement learning, preference optimization, or rule-guided behaviors.

Team Leadership

  • Serve as the future founding technical lead of the Foundational Model Science Program.
  • Mentor scientists and engineers and eventually build a specialty modeling team.
Why Mayo Clinic

Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans - to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.

Benefits Highlights
  • Medical: Multiple plan options.
  • Dental: Delta Dental or reimbursement account for flexible coverage.
  • Vision: Affordable plan with national network.
  • Pre-Tax Savings: HSA and FSAs for eligible expenses.
  • Retirement: Competitive retirement package to secure your future.
Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is. 

Equal Opportunity

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the "EOE is the Law".  Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

Required

  • PhD in Machine Learning, Computer Science, Applied Mathematics, or related discipline  with at least four years of informatics, Artificial Intelligence, data science and/or machine learning.
  • Experience with generative modeling, reasoning models, or multimodal foundation models.
  • Expertise in alignment methods (contrastive learning, RLHF/RLCS, preference optimization).
  • Experience with distributed training, and large-scale compute.

Preferred

  • Experience with clinical or EMR data across multiple modalities.
  • 7+ years experience training deep learning models, including transformers or multimodal architectures.
  • Experience defining evaluation frameworks for reasoning, multimodal synergy, reliability, or fairness.
  • Publications in multimodal learning, foundation models, or reasoning architectures.

What Mayo Clinic employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Mayo Clinic logo

About Mayo Clinic

Sourced by ZipRecruiter

Mayo Clinic is the largest integrated, not-for-profit medical group practice in the world. We're building the future, one where the best possible care is available to everyone — and more people can heal at home. Our relentless research turns into earlier diagnoses and new cures. That's how we inspire hope in those who need it most. At Mayo Clinic, experts work together to solve the most challenging unmet needs of patients. Our history of innovation dates back almost 150 years, when brothers Will and Charlie Mayo pioneered an integrated, team-based approach to medicine. Today, that trailblazing spirit drives innovations like Mayo Clinic Platform — which powers new technologies to change how care is delivered to all.

Industry

Hospitals

Company size

10,000+ Employees

Headquarters location

Rochester, MN, US

Year founded

1919