Data and Engineering Manager

University of Chicago

Full-time - Mid Level

Educational Services

About the position

The Data and Engineering Manager will lead our internal engineering team across our research initiatives at the Data Science Institute of the University of Chicago. This position is critical as we expand our engineering capacity and headcount. The successful candidate will not only establish and nurture software development best practices but will also be excited about the opportunity to build and grow a team in a dynamic academic environment. They will possess significant technical expertise in areas such as cloud computing, database design, web-based applications, or machine learning. The engineering manager will have substantial decision-making authority regarding project selection and execution. Working closely with the Executive Director of the Data Science Institute, the Chief of Staff, and the Director of the Data Science Clinic, this position will evaluate external proposals based on their technical merit, costs, and value. The Data and Engineering Manager will provide critical feedback that informs the growth direction of the Data Science Institute. Additionally, this role is externally facing, collaborating directly with researchers, students, postdocs, and industry and social impact partners. The position will involve approximately 30% project management (including scoping, discussions with partners, planning, and reporting), 30% development activities (code review, mentoring engineers and data scientists), and 40% direct contribution to projects.

Responsibilities

• Manage a team of engineers and students contributing to projects across the Data Science Institute's activities of research, education, and outreach driving the development of robust, scalable, core components.
• Provide mentorship to engineers and students and share your passion for staying on top of tech trends, experimenting with and learning new technologies.
• Establish processes to triage bugs, track software defects, and ensure their timely resolution.
• Define and steward technical standards and code quality.
• Oversee internal computing resources.
• Work closely with faculty, staff, and external organizations to develop novel research and act as the principal liaison to faculty research partners.
• Collaborate with external data science partner organizations on engineering projects.
• Develop, apply and communicate standards for evaluating project proposals based on technical merit and other institutional goals.
• Develop and communicate program priorities and performance standards and assess operations using these criteria.
• Participate and direct code review and code evaluation activities.
• Act as a subject matter expert and technical lead on one or more areas of database design, cloud deployment, microservices, devops best practices.
• Manage employees by establishing annual performance goals, allocating resources, assessing annual performance, and determining individual merit, incentive and/or promotional increases.
• Provide technical oversight and develop standards, guidelines, and processes for application systems.
• Advise decisions on project and infrastructure needs, including the evaluation of server technologies, languages, platforms, and frameworks.
• Develop timelines and project plans for the team.
• Perform other related work as needed.

Requirements

• Minimum requirements include a college or university degree in a related field.
• Minimum requirements include knowledge and skills developed through 7+ years of work experience in a related job discipline.

Nice-to-haves

• Bachelor's degree or graduate degree in math, statistics, computer science, data science, or related field.
• Over 3 years of professional software development management experience.
• Project management experience using agile methodologies (scrum, Kanban, etc.).
• Experience with research universities or research environments; experience working with faculty, students, and researchers.
• Student mentoring experience.
• Experience using and developing on one of the major cloud providers (AWS, GCP or Azure).
• Significant experience developing code in Python with knowledge of Node.js and a compiled language such as C/C++.
• Strong foundation in data management and data science.
• Cloud computing cost estimation and budgeting.
• Strong analytical skills and problem solving.