Research Software and Data Engineer

Job Description Summary This position is available within the University of Maryland’s Division of Information Technology (DIT). Overview:
The Research Computing team, part of the University of Maryland’s Division of Information Technology (DIT), designs and supports advanced technology systems and services used by researchers at UMD - a top 20 public research institution. The Research Software and Data Engineer will play a key role in designing, implementing, and supporting research cyberinfrastructure, software, and data-facing solutions.

The Research Software and Data Engineer's primary responsibilities will be to work with researchers to design, plan, and implement secure, compliant, and well-engineered software, data workflows, and data science-focused solutions that enrich research productivity, reliability, and reproducibility. The engineer will be part of short- to long-term projects. The work will also include consulting with researchers across disciplines in order to deeply understand their software and data needs and to identify and explain solutions.

The Research Software and Data Engineer will work with other team members to offer a wide range of related training workshops and to help bring a mature project management approach to research software work on campus, contributing toward software design and project planning and tracking. The Engineer will also write code to automate cloud account management, such as provisioning new cloud accounts.

The Engineer will work with researchers to adapt existing workflows to cloud environments. As a Research Computing team member, they will provide technical expertise and insight to teams and projects alongside research programs, collaborate across multiple units in the Division of IT and the University, and help researchers navigate the tools, processes, and services available to them.

N/A

Bachelor’s degree from an accredited college or university.

Three to five years experience working in software and data engineering environments.

Additional work experience as defined above may be substituted on a year for year basis for up to four (4) years of the required education.

• Batch processing
• Relational Database architectures
• Data Science tools
• Data pipelines, ETL, and data workflows

Knowledge of machine learning frameworks such as PyTorch, Tensor Flow, and JAX.

Knowledge of creating and operating container based infrastructure; knowledge of Docker or similar technology.

Knowledge of GPU programming.

Skill in programming, particularly in the languages used in our computational research applications (Julia programming language, C/C++, FORTRAN, python, R).

Skilled at providing technical solutions to complex problems in diverse computing environments.

Skill in oral and written communication.

Skill in the use of Google and Microsoft Office products.

Ability to learn new programming languages and technologies beyond area of core knowledge.

Ability to effectively communicate technical concepts with non-technical audiences.

Ability to multitask while demonstrating a commitment to customer service.

• Thorough knowledge of software lifecycle and software engineering best practices (sprints, code reviews, testing)
• Thorough knowledge of data science methods
• Ability to communicate with both technical and non-technical clients
• Experience with version control systems and issue trackers
• Experience with cloud platforms, to include code development, familiarity with APIs, user management
• Experience implementing/operating with controls for NIST SP 800-171, HIPAA Security and Privacy…