Jr DevOps Engineer- Interoperability

Health Catalyst•Salt Lake, UT

About The Position

Join one of the nation’s leading and most impactful health care performance improvement companies. Over the years, Health Catalyst has achieved and documented clinical, operational, and financial improvements for many of the nation’s leading healthcare organizations. We are also increasingly serving international markets. Our mission is to be the catalyst for massive, measurable, data-informed healthcare improvement through: Data: integrate data in a flexible, open & scalable platform to power healthcare’s digital transformation Analytics: deliver analytic applications & services that generate insight on how to measurably improve Expertise: provide clinical, financial & operational experts who enable & accelerate improvement Engagement: attract, develop and retain world-class team members by being a best place to work This position is currently not eligible for visa sponsorship. As a Junior Interoperability DevOps Engineer, you'll help support the systems and processes that enable reliable healthcare data exchange across our client ecosystem. Working alongside experienced engineers, implementation teams, and healthcare interoperability experts, you'll gain hands-on experience with cloud technologies, automation, clinical data processing, and production support. This role is an excellent opportunity for an early-career engineer who enjoys solving technical problems, learning new technologies, and contributing to solutions that improve healthcare outcomes. You'll help ensure clinical data moves accurately and efficiently while developing valuable skills in AWS, SQL, Python, automation, and healthcare interoperability.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, Healthcare Informatics, or a related technical field, or equivalent experience.
1-3 years of experience in software engineering, technical support, cloud operations, data engineering, DevOps, implementation support, or a related technical role.
Basic understanding of cloud platforms, preferably AWS.
Foundational SQL skills with the ability to query and analyze data.
Experience with Python or another scripting language.
Strong analytical and problem-solving abilities.
Effective verbal and written communication skills.
Ability to learn new technologies in a fast-paced environment.
Strong organizational skills and attention to detail.

Nice To Haves

Experience with AWS services such as S3, Athena, Lambda, or CloudWatch.
Exposure to healthcare IT, healthcare data, or interoperability concepts.
Familiarity with HL7, FHIR, CCD, C-CDA, or related healthcare standards.
Experience supporting client implementations or technical projects.
Familiarity with monitoring, logging, and operational support tools.
Exposure to automation, scripting, or data-processing workflows.
Experience using AI-assisted tools for development, research, testing, or documentation.

Responsibilities

Support implementation testing, validation, and go-live activities for new client deployments.
Review clinical documents and metadata to identify potential data quality or configuration issues.
Assist with validating patient, organization, facility, custodian, OID, and MRN mappings.
Document findings and communicate issues to project teams and senior engineers.
Help troubleshoot implementation-related issues and support production stabilization efforts.
Assist with AWS-based workflows utilizing services such as Amazon S3 and Athena.
Develop and maintain scripts and automation using Python, SQL, and related technologies.
Support the creation of technical documentation, runbooks, and support procedures.
Use AI-assisted tools to support development, troubleshooting, testing, and documentation activities.
Partner with senior engineers to identify opportunities to reduce manual processes through automation.
Support historical clinical data migrations and loading activities.
Assist with validating source files, inventories, manifests, and reconciliation processes.
Investigate data discrepancies, processing failures, and missing records.
Document validation results and implementation outcomes to ensure data accuracy.
Monitor system performance, processing volumes, queues, and operational dashboards.
Troubleshoot issues related to cloud storage, data processing, and system integrations.
Participate in incident response and root-cause analysis activities.
Help identify opportunities to improve reliability, visibility, and operational efficiency.
Support ongoing maintenance and monitoring of production environments.