Data Analytics Platform Engineering Lead

Duke Clinical Research Institute; Durham (NC); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Duke University’s Office of Information Technology seeks an Engineering Manager for the Data Analytics Practice to lead a team building enterprise data platforms that power reporting, analytics, decision-making, and emerging AI initiatives across the university.

You will shape data engineering strategy, mentor a high-performing team, and partner with technical and business leaders to deliver scalable, secure data solutions. A hybrid work arrangement is available.

Qualifications

• Bachelor's degree in Computer Science, IT, Engineering, Data Science or related field, or equivalent experience.
• Significant experience leading technical teams with large-scale data engineering initiatives.
• Experience with enterprise data warehouses, data lakes, or modern analytics platforms.
• Strong knowledge of SQL, Python, data modeling, and data integration practices.
• Experience with SDLC practices, source control, automated testing, and CI/CD.
• Ability to manage technical roadmaps, priorities, and stakeholder relationships.

Responsibilities

• Lead a team of data engineers responsible for enterprise data platform solutions.
• Define technical strategy, standards, and best practices for data architecture and analytics delivery.
• Partner with business and technical stakeholders to prioritize and deliver high-impact data initiatives.
• Support evolution of the enterprise data ecosystem to enable analytics, reporting, and AI capabilities.
• Drive operational excellence through automation, governance, platform reliability, and continuous improvement.

Skills

SQL

Python

Data modeling

Data integration

Education

Bachelor's degree in Computer Science or related field

Tools

dbt

Cloud platforms

Job description

Duke University’s Office of Information Technology seeks an Engineering Manager for the Data Analytics Practice to lead a team building enterprise data platforms that power reporting, analytics, decision-making, and emerging AI initiatives across the university.

You will shape data engineering strategy, mentor a high-performing team, and partner with technical and business leaders to deliver scalable, secure data solutions. A hybrid work arrangement is available.