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UVM Medical Center

DataOps / Platform Engineer

South Burlington, VT, United States

Salary Range: Min $52.34 Mid $65.43 Max $78.51

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Job details

Pay: Salary Range: Min $52.34 Mid $65.43 Max $78.51
Apply by: Nov 11, 2026
Education: Bachelor’s degree
Experience: 4+ years of experience in data platform operations, DataOps, or cloud infrastructure roles.
Posting language: English
Posted: Oct 29, 2026

Original job description

Building Name: UVMMC - 40 IDX Drive

Location Address: 40 IDX Drive, South Burlington Vermont

Regular

Department: UVMHN Data & Analytics: Data Platform & Engineering

Full Time

Standard Hours: 40

Biweekly Scheduled Hours:

Shift: Day

Primary Shift: -

Weekend Needs: None

Salary Range: Min $52.34 Mid $65.43 Max $78.51

Recruiter: Chelsea Therrien

Job Summary:

UVM Health is seeking an experienced, hands-on engineer to build, automate, secure, and operate the infrastructure and delivery capabilities behind our enterprise data platform. This senior individual-contributor role connects data engineering, cloud infrastructure, and production operations so that data products can be deployed safely, monitored effectively, recovered reliably, and supported over time.

Required platform proficiencies include at least 5 years of hands-on experience in each of AWS, Databricks, and Snowflake, plus at least 5 years of Microsoft data-platform engineering experience across Microsoft Fabric and related technologies, including demonstrated hands-on Fabric proficiency. Experience with multiple platforms may overlap within the same employment period; the platform minimums are not additive years beyond the overall experience requirement.

You will own the engineering and day-to-day operability of assigned data-platform services, working closely with data engineers, enterprise IT, cybersecurity, architecture, analytics teams, and implementation partners. You will help modernize the platform while maintaining continuity for existing data delivery, translating architecture into working infrastructure, repeatable deployments, effective controls, and documented operating practices.

This is not primarily a reporting, dashboard development, or ETL development position. Success requires direct experience building and operating the environments, automation, security controls, and recovery capabilities that production data engineering depends on.

Education:

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field required.

Experience:

4+ years of experience in data platform operations, DataOps, or cloud infrastructure roles.
Experience with Microsoft Fabric, Azure infrastructure, or equivalent cloud data platforms.
Experience designing and managing backup, archiving, and disaster recovery processes.
Familiarity with job scheduling, monitoring, and alerting tools.
Experience working in agile product delivery preferred.

Application guidance

Please make your relevant experience clear in your resume or application, including the years you have spent in data engineering, cloud computing, cloud infrastructure, and direct DataOps or platform engineering responsibilities. Describe the production environments you personally built or operated, the automation you implemented, and your responsibility for releases, incidents, security controls, and recovery. Identify your hands-on experience separately for AWS, Databricks, and Snowflake, including dates and engineering responsibilities for each. For the Microsoft requirement, distinguish direct Fabric experience from related Azure Synapse Analytics, Azure Data Factory, or Power BI engineering experience and explain how the combined experience meets the five-year minimum. We value specific examples of ownership and engineering outcomes over lists of tools. Job titles may vary; the scope and depth of your work must demonstrate the required experience.

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More about this job

Skills

Data engineering
AWS
Databricks
Snowflake
Cybersecurity
Reporting
Computer science
Microsoft Azure
Implement ICT recovery system
Scheduling
Cloud computing
Google Analytics
Microsoft Azure Data Factory
Microsoft Power BI

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