Analytics engineer

The Associate Director, Analytics Engineer supports Chicago Booth's marketing and institutional research team in building a data-driven culture by developing and maintaining robust data pipelines and analytics infrastructure. This role collaborates cross-functionally to centralize, clean, transform, and integrate data from multiple sources to unlock actionable insights that drive strategic decision-making. As a bridge between engineering, analytics, and data science, the Analytics Engineer ensures high data quality, develops comprehensive dashboards, and empowers stakeholders at all levels to leverage data effectively while adhering to privacy and security standards.

The compensation range for this position is $75K - $90K (depending on experience and skills).

PRINCIPAL DUTIES AND RESPONSIBILITIES:

1. Design, build, and maintain automated, reliable ETL pipelines and centralized data models to support analytics and reporting needs across the institution.
2. Partner with internal teams and stakeholders to collect, integrate, and validate data from diverse systems (e.g., SLATE CRM, digital analytics tools, advertising, survey platforms, among others).
3. Clean, organize, and transform data; perform detailed data quality assurance and proactively monitor and resolve data integrity issues.
4. Develop and maintain user-friendly data visualizations and executive dashboards using tools such as Tableau, custom script-based tools, or equivalent platforms.
5. Serve as a Subject Matter Expert (SME) for analytics, providing training and support to team members and stakeholders on data tools and best practices.
6. Translate ambiguous business requirements into clear, actionable technical specifications and deliver data solutions that address organizational needs.
7. Build and maintain comprehensive technical documentation covering data processes, models, and workflows to enable knowledge transfer and scalability.
8. Lead or participate in the design, execution, and analysis of surveys and digital marketing effectiveness studies.
9. Stay current with emerging trends and tools in data engineering, analytics, and digital measurement; recommend and implement process improvements.
10. Ensure all data handling complies with institutional data privacy, security policies, and industry best practices.

KNOWLEDGE, SKILLS AND EXPERIENCE:

1. Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field required. Master’s degree preferred.
2. A minimum of 2 years of relevant experience in data engineering, analytics engineering, or a similar technical analytical role.
3. Advanced proficiency in SQL for data transformation, analysis, and query optimization (e.g., window functions, debugging, performance tuning) required.
4. Strong experience using Python (or equivalent languages such as R) for data processing, transformation, and automation required.
5. Proficiency with modern ETL, data integration, and data modeling tools (e.g., dbt, FiveTran, Databricks) and version control systems (e.g., Git) required.
6. Demonstrated experience building and maintaining dashboards and reports in BI tools, such as Tableau required.
7. Working knowledge of digital analytics platforms (e.g., Google Analytics, Adobe Analytics) and marketing data sources preferred.
8. Understanding of Apache NiFi, big data platforms, particularly within Apache Hadoop ecosystem preferred.
9. Experience supporting data users, troubleshooting technical issues, and delivering data training and documentation.

“The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination .

Job seekers in need of a reasonable accommodation to complete the application process should call 773-834-3988 or email [email protected] with their request.”