Remote Data And Analytics Jobs
Remote Data And Analytics jobs are in steady demand across the U.S., with remote-first firms, distributed tech teams, and companies in finance, healthcare, and software hiring for these roles. Employers hiring remotely right now include CVS Health, Tailored Brands, and Praescient Analytics. Find a role that fits below and apply directly.
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Showing 5 of 146+ Remote Data And Analytics jobs
CityRochester
StateMN
RemoteYES
DepartmentDigital
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.
- 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.
Responsibilities
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.
Exemption Status
Exempt
Compensation Detail
$155,500.80 - $225,492.80/ year. Education, experience and tenure may be considered along with internal equity when job offers are extended.
Benefits Eligible
Yes
Schedule
Full Time
Hours/Pay Period
80
Schedule Details
M-F daytime hours 100% remote role, the employee needs to live within the US.
Weekend Schedule
As business needs dictate
International Assignment
No
Site Description
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.
Recruiter
Laura Percival
CityRochester
StateMN
RemoteYES
DepartmentDigital
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.
- 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.
Responsibilities
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.
Exemption Status
Exempt
Compensation Detail
$155,500.80 - $225,492.80/ year. Education, experience and tenure may be considered along with internal equity when job offers are extended.
Benefits Eligible
Yes
Schedule
Full Time
Hours/Pay Period
80
Schedule Details
M-F daytime hours 100% remote role, the employee needs to live within the US.
Weekend Schedule
As business needs dictate
International Assignment
No
Site Description
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.
Recruiter
Laura Percival
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Find JobsRemote Data And Analytics Job Market
Who's Hiring
- CVS Health19
- Tailored Brands5
- Praescient Analytics5
- JBS INTERNATIONAL5
- Extend3
Top Industries Hiring
- Technology & Software
- Insurance
- Electronics & Hardware
- Consulting & Professional Services
- Retail
What Employers Look For
The qualifications that appear most often in remote data and analytics jobs.
- Proficiency in SQL for querying and transforming relational data
- Experience with Python or R for data analysis and automation
- Hands-on work with BI tools such as Tableau, Power BI, or Looker
- Familiarity with cloud data platforms like Snowflake, BigQuery, or Redshift
- Bachelor's degree in statistics, mathematics, computer science, or a related field
- Ability to communicate data findings clearly to non-technical stakeholders
Tips for Your Remote Data And Analytics Job Search
Show async communication in your portfolio
Remote data and analytics teams depend on written handoffs and documented analysis. Include a sample report, dashboard with written commentary, or a README that explains your methodology. Employers want proof you can communicate findings without a meeting.
Apply early to remote roles that fit
Migrate Mate lists remote data and analytics openings from across the U.S. in one place. Search roles that match your stack and experience level and apply directly, without waiting to refine or over-prepare. Early applicants get more attention on competitive remote postings.
Highlight cloud and remote-tool fluency
Remote data and analytics employers expect hands-on experience with cloud platforms like AWS, GCP, or Azure alongside tools like dbt, Airflow, or Looker. Name the specific stack you've used in your resume, since remote teams hire for immediate productivity with minimal ramp-up.
Prepare for async technical screens
Many remote data and analytics interviews include take-home SQL or Python exercises and recorded video responses instead of live calls. Practice writing clean, commented code and explaining your reasoning in writing, since hiring managers evaluate both the answer and how clearly you document it.
Remote Data And Analytics Jobs: Frequently Asked Questions
How do I get a remote data and analytics job?
Target companies that already run distributed teams, since they've built the workflows that make remote data and analytics roles function well. Remote employers screen for self-direction, clear written communication, and the ability to document findings without hand-holding. Proficiency in SQL, Python, and cloud-based BI tools like Looker or Tableau signals readiness. A portfolio of projects with written context gives you a concrete edge over candidates who only list skills.
Which companies hire remote data and analyticss?
Companies hiring remote data and analyticss right now include CVS Health, Tailored Brands, and Praescient Analytics, based on current remote listings on Migrate Mate as of August 2026. Remote-first technology firms, distributed SaaS companies, and healthcare and financial services organizations with global teams are among the most consistent sources of remote data and analytics openings.
Can you get a remote data and analytics job with no experience?
Yes, but remote entry-level data and analytics roles are harder to land because employers expect you to work independently from day one without in-person guidance. Remote-first startups and mid-size tech companies are the most likely to hire entry-level candidates remotely. A portfolio of personal or open-source data projects, completed online certifications, and demonstrated async communication skills can substitute for formal experience and open the door.
Do you need a degree for remote data and analytics jobs?
Not always. Many remote employers weigh demonstrated skills and real project work as heavily as a degree, particularly in technology and SaaS companies where output is measurable. Proficiency in SQL, Python, data visualization tools, and the ability to communicate findings clearly in writing matter more to most remote hiring managers than the credential itself. A strong portfolio often does more than a diploma.
Which industries hire the most remote data and analyticss?
Most remote data and analytics openings sit in Technology & Software, Insurance, and Electronics & Hardware, per current remote listings on Migrate Mate as of August 2026. These sectors rely on distributed teams that need to analyze data across time zones and geographies, making remote data and analytics roles a natural fit for how they operate.
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