Job Description

Job Summary:

The Senior Research Facility Data Management Engineer is a senior-level individual contributor responsible for designing, implementing, and improving secure, scalable research data workflows for research core facilities, large research centers, and complex laboratory environments. This role sits at the intersection of research, technology, and security—helping researchers move data reliably from instruments and workstations to centrally supported storage, computing, and collaboration services. The position requires technical depth, sound judgment, and the ability to influence solutions across teams without direct supervisory responsibility.

In this position, you will serve as a trusted partner to researchers, core facility staff, endpoint management teams, research data specialists, cybersecurity colleagues, and cyberinfrastructure teams. You will independently assess complex research workflows, recommend practical and secure approaches, and help implement solutions for user workstations, lab instrument computers, legacy operating systems, virtual firewall protections, data staging, transfer, and long-term storage.

Specific Responsibilities:

Serve as a data management expert for research data workflow design, endpoint coordination, and secure data movement in support of research core facilities and research centers. Guide researchers and facility staff in adopting centrally supported storage, compute, collaboration, and data transfer services that fit their data volume, sensitivity, and collaboration needs.
Lead technical discovery and requirements gathering with researchers, core facility leaders, vendors, and IT partners to translate scientific needs into practical, supportable solutions. Independently assess complex research environments, including user workstations, shared lab systems, and specialized lab instrument computers, and recommend secure, sustainable support models.
Identify recurring needs across facilities and research centers and contribute to reusable service models, standards, templates, and best practices. Design and implement secure approaches for legacy or specialized instrument systems, including systems that require network isolation, virtual firewall protections, constrained access, or customized data transfer workflows.
Develop proof-of-concept solutions, evaluate technical options, and recommend supportable service patterns when standard institutional tools do not fully meet research requirements.
Create and deliver user documentation, diagrams, onboarding resources, training, and guidance tailored to researchers, core facility staff, IT partners, and other audiences with varied technical backgrounds.
Work across teams to facilitate or provide support – from instrument acquisition through staging, quality review, transfer, storage, sharing, and eventual placement in lab-owned or centrally managed storage environments.
Lead technical work by coordinating research computing, endpoint management, cybersecurity, networking, storage, and support teams; communicating recommendations, tradeoffs, risks, status, and outcomes; and driving cross-functional efforts toward practical, supportable solutions.
Miscellaneous

Performs other duties as assigned.

Minimum Qualifications:

Education: Successful completion of a full four-year course of study in an accredited college or university leading to a bachelor's degree in a related field, or equivalent combination of education and experience.

Demonstrated experience supporting or using complex technical environments, preferably in research computing, academic research, scientific laboratories, core facilities, or data-intensive settings.

Minimum Competencies: (Skills, knowledge, and abilities.)

Working knowledge of Windows, macOS, and Linux systems, including support considerations for mixed environments, instrument-attached systems, and legacy operating systems.
Demonstrated ability to design, troubleshoot, and improve research data workflows involving endpoints, instruments, network paths, storage systems, and/or transfer tools.
Demonstrated proficiency with scripting or programming languages such as Python, Bash, or PowerShell for automation, integration, workflow validation, or operational support.
Experience with data transfer tools and protocols such as Globus, SFTP, rsync, SMB, NFS, or comparable technologies for reliable movement of research data.
Experience with cloud and enterprise platforms such as AWS, Azure, Google Cloud, Microsoft 365, or comparable services, especially for storage, collaboration, data transfer, or secure workflow support.
Working knowledge of information security practices relevant to data environments, including access control, least privilege, network segmentation, endpoint protections, secure data handling, and compensating controls for legacy systems.
Demonstrated ability to exercise independent judgment, evaluate tradeoffs, and make practical recommendations that balance requirements, usability, sustainability, security, and compliance.
Demonstrated ability to lead work through influence, coordinate cross-functional efforts, communicate recommendations clearly, and move ambiguous technical work toward clear outcomes across teams.
Experience creating documentation, diagrams, training materials, operational procedures, and onboarding resources for technical and non-technical audiences.