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Remote Dataops Engineer Jobs in Minnesota (NOW HIRING)

Remote Dataops Engineer information

What is the difference between Remote Dataops Engineer vs Data Engineer?

AspectRemote Dataops EngineerData Engineer
CredentialsBS in CS, Data Science, or related; certifications like AWS, GCP, or AzureSimilar credentials; often with additional database or software engineering certifications
Work EnvironmentRemote or hybrid, collaborative teams, cloud platformsRemote or on-site, data-focused teams, cloud and on-prem infrastructure
Industry UsageTech, finance, healthcare, e-commerceTech, finance, retail, telecom
Search & Comparison IntentUnderstanding roles in data operations, cloud deployment, automationFocus on data pipeline development, database management, ETL processes

The Remote Dataops Engineer and Data Engineer roles share many credentials and work environments, often overlapping in cloud and data infrastructure. However, Data Engineers typically focus more on building and maintaining data pipelines and databases, while Dataops Engineers emphasize automating deployment, monitoring, and optimizing data workflows in cloud environments.

What is a remote DataOps engineer?

A Remote DataOps Engineer is a technology professional who works remotely to manage, automate, and optimize data pipelines and processes within an organization. Their main goal is to streamline the flow of data between various systems, ensuring the availability, quality, and security of data for analytics and business operations. They collaborate closely with data engineers, analysts, and IT teams to develop efficient workflows, automate repetitive tasks, and monitor data infrastructure performance. By working remotely, they leverage cloud-based tools and communication platforms to support distributed teams and global data operations.

How do remote DataOps engineers typically collaborate with cross-functional teams to ensure smooth data pipeline operations?

Remote DataOps Engineers often work closely with data engineers, analysts, and DevOps teams using collaboration tools like Slack, Jira, and GitHub. Regular virtual meetings and documentation are essential to align on pipeline requirements, monitor data quality, and resolve issues quickly. Clear communication and proactive status updates help build trust with stakeholders and ensure that data infrastructure supports business needs efficiently, even when working remotely.

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

To thrive as a Remote DataOps Engineer, you need expertise in data engineering, automation, and pipeline management, typically backed by a degree in computer science or a related field. Familiarity with tools like Apache Airflow, Kubernetes, CI/CD systems, and cloud platforms such as AWS or Azure is highly valued, along with relevant certifications. Excellent problem-solving, communication, and collaboration skills are crucial for managing distributed teams and complex data workflows. These skills and qualities ensure efficient, reliable, and scalable data infrastructure essential for modern data-driven organizations.
What are popular job titles related to Remote Dataops Engineer jobs in Minnesota? For Remote Dataops Engineer jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Remote Dataops Engineer jobs in Minnesota look for? The top searched job categories for Remote Dataops Engineer jobs in Minnesota are:
What cities in Minnesota are hiring for Remote Dataops Engineer jobs? Cities in Minnesota with the most Remote Dataops Engineer job openings:
Infographic showing various Remote Dataops Engineer job openings in Minnesota as of July 2026, with employment types broken down into 11% Locum Tenens, 13% Internship, 6% As Needed, 42% Full Time, 4% Part Time, and 24% Nights. Highlights an 67% Physical, 9% Hybrid, and 24% Remote job distribution.

Principal Data Engineer - Enterprise Data & Analytics - Remote

Mayo Clinic

Rochester, MN • On-site, Remote

$111K - $134K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 9 days ago


Mayo Clinic rating

7.8

Company rating: 7.8 out of 10

Based on 696 frontline employees who took The Breakroom Quiz

132nd of 887 rated healthcare providers


Job description


The Principal Data Engineer serves as a hands-on technical authority responsible for defining and implementing enterprise-scale data architecture and engineering strategies while actively contributing to solution design, development, optimization, and technical delivery. As part of an assigned product team, this role develops and deploys data pipelines, integrations, and transformations to support analytics and machine learning applications using open-source programming languages and vendor software. The position requires a strong understanding of the organization's current solutions, coding languages, tools, and Enterprise Data and Analytics technology framework, as well as the ability to apply independent judgment, provide consultative services to departments, divisions, and leadership committees, and partner with product owners and Analytics and Machine Learning delivery teams to identify and retrieve data, conduct exploratory analysis, transform data, visualize trends, build and validate analytical models, and translate qualitative and quantitative assessments into actionable insights.
Key responsibilities:
These positions are hands-on engineering roles. In this role, employees are expected to actively design, develop, review, and optimize production code and platform capabilities while providing technical leadership and mentorship to engineering teams.
Qualifications
A Bachelor's degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of seven years of professional or research experience in data visualization, data engineering, analytical modeling techniques; OR an Associate's degree in a relevant field such as engineering, mathematics, computer science, information technology, health science, or other analytical/quantitative field and a minimum of nine years of professional or research experience in data visualization, data engineering, analytical modeling techniques. In-depth business or practice knowledge will also be considered.
Incumbent must have the ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends and enterprise changes. Interpersonal skills, time management skills, and demonstrated experience working on cross functional teams are required. Requires strong analytical skills and the ability to identify and recommend solutions and a commitment to customer service. The position requires excellent verbal and written communication skills, attention to detail, and a high capacity for learning and problem resolution. Advanced experience in SQL is required. Advanced Experience in scripting languages such as Python, JavaScript, PHP, C++ or Java & API integration is required. Experience in hybrid data processing methods (batch and streaming) such as Apache Spark, Hive, Pig, Kafka is required. Experience with big data, statistics, and machine learning is required. The ability to navigate linux and windows operating systems is required. Knowledge of workflow scheduling (Apache Airflow Google Composer), Infrastructure as code (Kubernetes, Docker) CI/CD (Jenkins, Github Actions) is required. Experience in DataOps/DevOps and agile methodologies is required. Experience with hybrid data virtualization such as Denodo is preferred. Working knowledge of Tableau, Power BI, SAS, ThoughtSpot, DASH, d3, React, Snowflake, SSIS, and Google Big Query is preferred.
The preferred candidate will possess:
  • Expert-level proficiency in Python and SQL with extensive experience developing enterprise-scale production systems.
  • Advanced expertise in scalable distributed computing frameworks and modern data processing platforms.
  • Advanced experience implementing and governing open data architectures utilizing Apache Iceberg, Delta Lake, Apache Hudi, and related technologies.
  • Deep understanding of modern analytical storage formats including Parquet, Avro, and ORC.
  • Demonstrated expertise in lakehouse architecture, data platform design, and large-scale data engineering practices.
  • Experience architecting and implementing cloud-agnostic solutions across multiple technology ecosystems.
  • Experience designing highly scalable, fault-tolerant, secure, and observable data platforms supporting analytics, AI, machine learning, and operational workloads.
  • Experience establishing enterprise engineering standards, architecture patterns, and modernization strategies.

About Us
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.

About the Team
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.

What Mayo Clinic employees say

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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