Research Data Engineer

University of Southern California•Los Angeles, CA

1d•$126,078 - $150,000•Onsite

About The Position

The University of Southern California (USC) Information Technology Services is seeking a Research Data Engineer to help build and advance the secure computing capabilities that enable cutting-edge research across USC. This is a hands-on opportunity to work at the intersection of research computing, data engineering, workflow automation, and secure data management, helping faculty and research teams turn complex data requirements into practical solutions. You'll play an important role in USC's expanding secure computing environment for sensitive and regulated research data. With more than 200 research projects across the university working with data subject to heightened security and compliance requirements, you'll help researchers manage, process, and use their data effectively while navigating increasingly complex research computing environments. Working directly with faculty, principal investigators, researchers, and students, you'll bring technical expertise to the full research lifecycle - from data collection and processing to advanced computing, workflow automation, and research outcomes. You'll also help shape how researchers interact with USC's secure computing services, streamline manual processes, and create scalable workflows that make sophisticated research infrastructure easier to use. If you enjoy solving complex data problems, building and automating computational workflows, and applying your technical skills in an environment where your work directly enables research and discovery, this is an opportunity to make an impact across USC's research community.

Requirements

Bachelor's degree.
Combined experience/education as substitute for minimum education.
2 years' work experience.
Demonstrated working knowledge of federal compliance regulations including FERPA, FISMA, NIST 800-171, NIST 800-53, DFARS/CMMC, etc.
2+ years of experience in research data management, data governance, IT compliances, or information security.
Experience with Linux system, scripting (pythoin, bash), databases (SQL, PostgresSQL, etc.).
Firm understanding of data modeling, master data management, enterprise data warehousing, ETL, reporting, querying, requirements analysis, and data integration techniques.
Understanding of database server architecture, administration, and security.
Ability to understand and work with large, complex IT systems.
Experience contributing to and managing development policies, from planning through execution.
Perseverance, drive and keen attention to detail.
Knowledge of network architecture.
Excellent written and oral communication skills, presenting technical topics in a technically-oriented detailed fashion to technical audiences.
Ability to develop positive working relationships and strong rapport with team members and stakeholders.
Demonstrated knowledge of the research process, proposal lifecycle, data lifecycle, and workflows.
Advanced knowledge in Linux/Unix and extensive experience in building, installing, and maintaining open source software in high-performance computing environment.
Proven expertise in Unix/Linux shell scripting and one or more programming language (e.g., C/C++, Python, Perl, MATLAB).
Strong debugging and troubleshooting skills.
Strong understanding of high-performance computing topics as well as the data and programming efforts involved in HPC/Cloud.
Experience communicating technical details to non-technical audiences (e.g., documentation, training, public speaking).
Proven ability to successfully manage and prioritize multiple projects and plans, implement project specifications, report project status, identify delays, and raise concerns.
Exceptional interpersonal skills, including demonstrated ability to interact effectively with a variety of stakeholders including researchers, IT staff, IT leadership, and university administrators.
Awareness of compliance regulations surrounding research data including federal requirements and granting agency standards.
Ability to develop positive working relationships and a strong rapport with team members.

Nice To Haves

Bachelor's degree in Computer Science, Computer Information Systems, or a related field; an advanced degree in computer science, information systems, science, engineering, biomedical computing, or a related computational discipline is highly desirable.
Four years of relevant professional experience.
Hands-on research experience, particularly within science, engineering, biomedical computing, or another computationally intensive research discipline.
Demonstrated understanding of the end-to-end research lifecycle and experience working directly with faculty, researchers, laboratories, or research teams.
Strong programming and scripting capabilities, particularly Python, with hands-on experience working in Linux environments.
Practical experience with SQL, databases, data processing, batch scripting, and workflow automation.
Experience developing or supporting sophisticated computational and data workflows in research or advanced computing environments.
Knowledge of research data security, data sensitivity, data classification, and regulated-data practices.
Familiarity with federal research or data-security frameworks such as FedRAMP and Controlled Unclassified Information (CUI) requirements is preferred but not required.
Ability to translate technical, data-management, and compliance requirements into practical processes and guidance for researchers who may not specialize in these areas.
Ability to work effectively across technical and research communities and communicate complex requirements to faculty, principal investigators, researchers, students, and technical partners.
Demonstrated experience conducting research in a higher education environment and providing technical support for research projects.
Familiarity with shared memory and distributed memory parallelism (e.g., OpenMP, MPI, OpenACC), accelerators (e.g., GPUs), and large-scale file systems.

Responsibilities

Design and manage secure data pipelines for ingestion, transformation, de-identification, and export of sensitive research datasets within approved computing enclaves.
Develop, implement, and maintain data management plan and data usage agreements that satisfy federal sponsor requirements (NSF, NIH, DoD, DoE, etc.).
Manage necessary documentation work including data management plan, usage agreement, SOPs, SSPs, POA&M for audits and sponsor reviews.
Coordinate with Cybersecurity Office for incident management.
Design and implement data architecture solutions that translate business and research requirements into conceptual, logical, and physical data models, prototypes, testing approaches, and sustainable processes.
Support faculty, principal investigators, researchers, and students with research data management and advanced computing workflows, including projects involving sensitive or regulated data.
Develop and maintain data architecture standards, protocols, frameworks, documentation, and techniques while performing root cause analysis and developing strategies to prevent recurring data-management issues.
Create and automate data-processing and research workflows that reduce manual effort and support efficient use of USC's secure computing environment.
Develop and deliver onboarding, training, and guidance to help researchers appropriately manage sensitive data and navigate secure research computing processes.
Partner with technical teams and stakeholders to define workflows for the secure computing user portal, including processes associated with research project setup and data-use requirements.
Research and recommend data tools, services, API integration approaches, and process improvements that advance USC's enterprise data and analytics capabilities.