Analytics Engineer, Data Analytics Practice

The Data Analytics Practice within Duke University's Office of Information Technology (OIT) is seeking an Analytics Engineer to help transform institutional data into meaningful insights, applications, and decision-support tools that advance Duke's academic, research, and operational missions.

Duke University depends on trusted data professionals to support strategic decision-making, improve business processes, and enable increasingly sophisticated analytics and artificial intelligence capabilities. The Data Analytics Practice brings together expertise in analytics, data engineering, database administration, and AI engineering to unlock the value of institutional data across the university.

In this role, you will work across diverse data domains to solve complex business problems, build analytical products, and create intuitive data experiences that help stakeholders explore information and make informed decisions. You'll collaborate closely with data engineers, AI engineers, researchers, and business partners while leveraging modern analytics and AI-assisted development tools to rapidly prototype and deliver impactful solutions. If you're naturally curious, enjoy solving ambiguous problems, and are passionate about turning data into action, we'd love to hear from you.

Minimum Requirements

• Bachelor's degree in Mathematics, Computer Science, Data Science, or another quantitative field, or an equivalent combination of education and experience.
• Minimum of two years of professional experience in data analytics, software development, engineering, or a related field.
• Proficiency in SQL and data analysis using Python, R, or a similar analytical programming language.
• Experience exploring, cleaning, transforming, and interpreting complex datasets.
• Experience building dashboards, reports, data visualizations, or interactive analytical applications.
• Experience working with Git and collaborative, version-controlled development practices.
• Understanding of common data formats and architectures, including JSON, CSV, Parquet, relational databases, data lakes, and dimensional modeling concepts.
• Strong written and verbal communication skills with the ability to explain technical and analytical concepts to diverse audiences.
• Demonstrated ability to manage projects independently and work effectively in a collaborative team environment.
• Strong documentation and organizational skills.

Preferred Qualifications

• Master's degree in Data Science, Computer Science, Analytics, Statistics, Mathematics, or a related quantitative discipline.
• Experience applying statistical modeling, predictive analytics, or machine learning methods to business or research problems.
• Experience working with AI-assisted development tools and coding agents.
• Experience developing reusable analytical applications, workflows, or data products.
• Experience working across multiple institutional or business data domains.
• Other Requirements
• Passion for turning complex data into practical insights and useful tools.
• Curiosity and willingness to learn emerging technologies, analytics methods, and AI-enabled tools.
• Ability to thrive in ambiguous environments and independently translate evolving requirements into scalable solutions.

Work Arrangement

• Hybrid eligible. Candidate must be available for weekly meetings in Durham, NC.
• This position does not offer visa sponsorship.

Be Bold.

What You'll Do

• Collect, analyze, and interpret institutional data to support research, operational decision-making, and strategic initiatives across the university.
• Explore and transform data from multiple sources to improve data quality, understand business logic, and uncover meaningful patterns, trends, and opportunities.
• Apply analytical techniques, statistical methods, and machine learning approaches to answer complex business questions and generate actionable insights.
• Design, build, test, and maintain analytical applications, dashboards, visualizations, and decision-support tools that enhance data accessibility and usability.
• Leverage AI-assisted development tools to accelerate application development while ensuring quality, maintainability, and accuracy.
• Manage projects from discovery through delivery, including requirements gathering, planning, stakeholder engagement, prioritization, testing, and implementation.
• Communicate findings and recommendations to technical and non-technical stakeholders, providing context around assumptions, limitations, and business implications.
• Develop and maintain clear documentation of data sources, analytical methods, business rules, and application functionality.
• Promote best practices that improve the quality, scalability, consistency, and efficiency of analytics work across the Data Analytics Practice.

As Analytics Engineer, you'll work alongside talented data professionals, engineers, and institutional partners to solve meaningful challenges, develop innovative analytical solutions, and help shape Duke's evolving data and AI ecosystem. You'll join a collaborative environment that values curiosity, continuous learning, innovation, and professional growth while making a measurable impact across the university.