Senior Analytics Engineer

Position Summary The Education Design and Informatics (EDI) team within the Office of Health Sciences Education at Vanderbilt University School of Medicine (VUSM) is seeking an experienced Analytics Engineer with an inquisitive and analytical mindset to join our team. The Analytics Engineer designs and maintains curated datasets and data models that support educational analytics, dashboards, and AI-enabled learning tools and predictive analytics across VUSM. The role involves building reproducible, version-controlled data transformation workflows that convert raw educational data into analysis-ready structures while ensuring data quality, governance, and transparency. A key responsibility is creating and maintaining Power BI dashboards and visualizations for educational leaders, administrators, and faculty that align with institutional competency frameworks and strategic goals. The Analytics Engineer collaborates with AI engineers, software developers, and cross-institutional stakeholders to enable predictive modeling, experimentation datasets, and learner-facing insights embedded in digital learning workflows. This position contributes to Vanderbilt’s broader precision education and AI-enabled learning strategy by translating educational questions into measurable data indicators and staying current with evolving data governance and analytics practices. This role offers opportunities to contribute to nationally recognized research in precision education and to develop expertise at the intersection of data engineering, artificial intelligence, and medical education within one of the nation’s leading academic medical centers. This position reports administratively and functionally to the Director of Education Design and Informatics. About the Work Unit The Office of Health Sciences Education (OHSE) administers the degree programs of the Vanderbilt University School of Medicine (VUSM) and supports its mission to catalyze impactful discovery, servant leadership, and lifelong learning. OHSE staff provide comprehensive support across academic program administration, educational design and informatics, student services, and financial and operational oversight. In alignment with VUSM’s commitment to excellence, OHSE works to prepare future leaders in the health professions who are equipped with the knowledge, skills, and judgment needed to deliver safe, effective, ethical, and patient-centered care. Our students are encouraged to think critically, foster innovation, and understand the broader systems and social factors that shape health outcomes—empowering them to advocate for positive change in both local and global communities. The Education Design and Informatics (EDI) team serves as the technology, data, and analytics arm of OHSE, building and maintaining the digital infrastructure, learning platforms, dashboards, and AI-enabled tools that support the educational mission. The Analytics Engineer joins a multidisciplinary EDI team that includes software developers, instructional designers, an applied AI engineer, and data specialists. Vanderbilt’s institutional strengths—including a top-tier health system, deep research infrastructure, enterprise Databricks and Epic EHR environments, and a strong commitment to innovation in medical education—provide a uniquely rich foundation for this work. Key Functions and Expected Performance Update and optimize VUSM’s cloud-based data architecture to support ongoing scalability, efficiency, and security standards Build and maintain processes that support data transformation, workload management, data structures, dependency, and metadata Support monitoring and alerting processes to ensure uptime of infrastructure Identify, design, and implement internal process improvements such as automating manual processes and optimizing data delivery Manage and communicate data visualization plans to internal team and stakeholders Collaborate with Development team on architectural decisions Perform data analysis required to troubleshoot data-related issues and assist in the resolution of data issues Design and maintain curated datasets that support educational analytics, dashboards, and AI feature development Develop and improve canonical tables and views representing learners, competencies, curricular experiences, assessments, progression metrics, and other medical education concepts Align data models with standard medical education frameworks and ontologies (e.g., AAMC competency frameworks, EPA/milestone mappings) to ensure interoperability and domain relevance Maintain comprehensive documentation of key data views and catalog table definitions within Databricks to ensure data transparency, governance, and accessibility across teams Build transformation workflows that convert raw data into analysis-ready structures Implement version-controlled data transformations using tools such as dbt, SQL-based pipelines, and Databricks workflows Ensure datasets are reproducible, documented, and auditable Monitor data quality, completeness, and consistency across sources Build and maintain Power BI dashboards and reporting views used by educational leadership, program administrators, and faculty Collaborate with stakeholders to understand analytic needs and to define meaningful visualizations and metrics Ensure that dashboards align with institutional competency frameworks and educational goals Iteratively refine dashboards and reporting views based on end-user feedback, evolving programmatic needs, and emerging data sources Work with the Applied AI Engineer to create feature-ready datasets supporting predictive models and AI applications Collaborate with stakeholders in VUIT, VUSM, and VUMC IT to facilitate secure cross-institutional exchange of educational datasets Collaborate with software developers to expose analytics datasets to VSTAR and related applications Support development of learner-facing insights and faculty analytics embedded in digital learning workflows Design and implement intervention signals and early warning indicators to support timely learner support Help design experimentation datasets for evaluating educational interventions and AI tools Contribute to evaluation frameworks that assess the effectiveness and impact of AI-enabled educational tools and interventions Translate educational questions into data models and measurable indicators Contribute to Vanderbilt’s broader strategy for precision education, learning analytics, and AI-enabled education Maintain clear documentation of data models, transformations, and metrics Stay current with evolving approaches to educational analytics, data modeling, and data governance Support grant-related activities including preparation of pilot data, data architecture documentation for proposals, and reporting on funded projects Supervisory Relationships This position does not have supervisory responsibility and reports administratively and functionally to the Associate Director, Education Design and Informatics. Education and Certifications Bachelor’s degree or above in Computer Science, Data Science, Informatics, Information Systems, Health Informatics, or related technical field OR a comparable combination of on-the-job experience and technical training is necessary. Experience and Skills 5 years of experience with data engineering, analytical data modeling, data transformations, or analytics engineering is necessary. 5 years of experience working in education, healthcare, or another complex regulated environment is preferred. 5 years of experience with Python, including object-oriented programming, is highly preferred. Advanced SQL skills and experience designing complex queries and transformations is highly preferred. Demonstrated skills with NoSQL databases (e.g., for unstructured assessment data or document stores) is preferred. Demonstrated experience working with cloud-based data platforms or modern data warehouses (Azure, AWS, GCP, Databricks, Snowflake) is highly preferred. Excellent oral and written communication skills with a keen sense of stakeholder engagement is highly preferred. Ability to translate stakeholder questions into structured datasets and metrics is highly preferred. Experience supporting and working with cross-functional teams in a dynamic, collaborative environment is highly preferred. Demonstrated ability to work with non-technical domain experts and navigate complex organizational structures is preferred. Experience supporting machine learning or feature engineering workflows is highly preferred. Experience with designing data models for dashboards and reporting through dimensional modeling techniques is highly preferred. Experience building or supporting dashboards in tools such as Power BI, Tableau, or similar platforms is preferred. Experience with continuous integration/continuous delivery automation and version control (Git) in Bitbucket, GitLab, GitHub, or Azure DevOps is preferred. Experience with REST data services, APIs, and microservices is preferred. Experience working with regulated or sensitive datasets (FERPA, HIPAA-adjacent environments) is preferred. Familiarity with competency-based education or learner progression frameworks is preferred. Familiarity with ethical considerations in educational data use, algorithmic fairness, or responsible AI practices is preferred. #J-18808-Ljbffr