Data Analytics Engineer, College of Natural Sciences

Data Analytics and Data EngineeringDevelops, 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.Collaboration, Communication, and Institutional KnowledgeWorks both independently and collaboratively with cross-functional teams to develop exceptional data products to meet university needs.Participates in 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.Handles confidential information with tact and discretion.