Data Analytics and Data Engineering:Develops, codes, validates, and implements relational databases and integrated data structures that support analytics.Collaborates with functional partners to collect business requirements and develop and refine business logic.Collaborates with technical partners to locate, clean, and orchestrate source data.Crafts code for the translation and transformation of functional business logic into a high-scale database environment that can readily support the production of descriptive, predictive, and prescriptive analytics and consumable reports, dashboards, and other tools to support University decision-making.Understands how to best design database structures for meaningful data visualizations and interactive tools.Engages in best practices in data analytics and data engineering including robust validation processes, testing/deployment procedures, algorithms for data mining, version control and code integration, thorough documentation, and automation and streamlining of data processing pipelines.Applies creativity and flexibility to finding solutions for new institutional data challenges.Assists with special projects and ad hoc data requests as needed.Analytical ArchitectureIn collaboration with reporting manager:Assists with diagramming analytics architecture strategy and roadmap, as well as translating strategy into actionable tasks.Coordinates the development, promotion, and implementation of select best practices in analytics architecture and data engineering examples include coding conventions, naming standards for analytical structures, performance tuning, review checklists.Engages in exploration, evaluation, and implementation of new/improved tools, features, and/or processes, to scale up analytics architecture including possible transition to an ETL tool.Collaboration, Communication, and Institutional Knowledge:Works both independently and collaboratively with cross-functional teams to develop exceptional data products to meet university needs.Participates in the Data Project Lifecycle from conception, requirements gathering and design, documentation, development and testing through deployment.Engages and communicates with partners and stakeholders to manage requests, expectations, and deliverables.Effectively communicates project status, progress, risks, and issues to drive project to completion.Develops an in-depth knowledge of university data processes and technologies.Consult with data analysts on specific data and coding questions within and outside of the team.Handles confidential information with tact and discretion.