IT Specialist (Health Policy and Management)

Johns Hopkins University•Baltimore, MD

5d•Remote

About The Position

We are seeking an IT Specialist who will participate in basic development, implementation, maintenance, support and documentation of various departmental and enterprise-wide application systems. This includes but is not limited to the installation, modification, and testing of new and/or upgraded applications (packages or home grown), operating systems, file structures, hardware, communication devices, and productivity tools. Under guidance assist in gathering and translating business requirements into functional/technical specifications and designs. Assists in maintaining databases and application system code. This is a casual position on the METRC Data Engineering team within the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health. METRC runs multiple longitudinal randomized clinical multi-site trials supported by an in-house Data Engineering shop. This role is a chance to see how that works from the inside. You will work under the direct guidance of our Senior Cloud Engineer and Developer II, contributing to real research software that supports active clinical trials. Domain experience in clinical research is not expected. If you have completed introductory coursework in programming, data management, and software development concepts, you will arrive with the foundational awareness needed to contribute meaningfully. We use Basecamp internally rather than JIRA; familiarity with either is welcome but neither is required, just awareness of this kind of software is required. As with our other developer roles, our software design patterns and development cycles follow the rhythms of study life cycles — meaning you will be supporting software that needs to remain functional and extensible across studies that may not yet be designed. We use a DataOps methodology rooted in Agile principles. As casual worker, your primary contribution will be in documentation, testing, and basic scripting tasks under close supervision, with the opportunity to apply and deepen your awareness of core development concepts in a real research engineering environment.

Requirements

High school diploma or graduation equivalent.
Introductory coursework in programming, data management, and software development concepts.
Awareness of Agile Methodology
Awareness of Algorithms
Awareness of CI/CD
Awareness of Code Review
Awareness of Data Structures
Awareness of Debugging
Awareness of Development Ops
Awareness of Software Development Life Cycle
Awareness of Unit Testing

Nice To Haves

Some project management experience.
Introductory coursework or projects in R or Python; familiarity with version control (Git).

Responsibilities

Gathers simple system requirements by meeting with clients and researching existing technology to understand the business requirements for new applications.
May assist with written documentation of findings to share with the client and other IT colleagues.
Follows defined task lists by using basic programming skills to complete projects of limited scope and meet required milestones.
May assist in writing functional specifications for use by programmers and business analysts to develop technical solutions.
Under guidance, change data input, files/database structures, data transformation, algorithms, and data output by using appropriate computer language/tools to provide technical solutions for simple application development tasks.
Assist with creating and documenting simple test scenarios using the appropriate testing tools to validate and verify application functionality.
Test changes by using the appropriate simple test scenarios to identify errors.
Maintain documentation materials that serve as technical and/or end-user references.
Provide basic application and desktop support by triaging and resolving simple issues to ensure prompt and effective service.
Other duties as assigned.
Assist with documentation and testing of custom R packages used for cleaning, analysis, and distribution of METRC study data.
Support basic data quality checks and validation tasks across study datasets under direct supervision.
Contribute to internal knowledge base documentation for data pipeline processes, making existing institutional knowledge more accessible to the team.