Lead Data Analyst - Craft Education

Western Governors University•Nashville, TN

13d•Onsite

About The Position

The Lead Data Analyst for Craft Education extracts, processes, analyzes, and reports on data to produce rigorous, actionable insights and research. The role builds relationships across IAR, Data Engineering, Product Management, Finance, EdTech, and Faculty staff; performs ad hoc analyses; develops standard reports and data visualizations; and communicates insights through data storytelling that helps accelerate action. The position is expected to work in Craft’s office in Downtown Nashville. The analyst works with cross-functional partners and leaders to clarify data and research needs, answer complex business questions, develop and interpret data models, and support data quality, visualization, and management practices. The position also contributes to colleagues’ development, advances projects with autonomy, supports strategic planning and operational excellence, and handles data responsibly and securely. Occasional travel of up to 20% is required, including attendance at designated company summits.

Requirements

Bachelor’s degree in a related discipline, or an equivalent combination of training, experience, credentials, or accomplishments demonstrating the ability to perform the job’s essential functions.
Seven years of related experience in Data Analysis, Business Intelligence, Data Science, Statistics, Decision Intelligence, Research, Learning Science, or Behavioral/Cognitive Psychology.
Advanced SQL proficiency, including queries and subqueries, creating and modifying views, join types, filtering, sorting, aggregation, window functions, common table expressions, and performance tuning.
High proficiency and experience with Tableau and Power BI for presenting data through charts, graphs, and maps to clarify trends, patterns, and outliers.
Ability to interpret and design data models describing relationships among data and the real-world entities represented.
Extensive experience with conceptual and logical data modeling, dimensional models, star and snowflake schemas, and slowly changing dimensions.
Familiarity with project management methodologies and frameworks such as Waterfall, Agile, and SDLC.
Proficiency in Microsoft Office, including advanced Excel knowledge.
Proficiency with flowcharting and diagramming tools such as Miro, Visio, and Lucidchart or similar applications.
Familiarity with relevant university KPIs and their drivers, and active participation in defining and tracking them.
Sound judgment, systems thinking, and analytical skills to assess risks, perform root-cause analyses, make recommendations, and support cross-functional decisions.
Ability to work with high autonomy, reliability, self-direction, and a bias for action; manage concurrent and conflicting activities with minimal supervision.
Ability to travel occasionally, up to 20%, including attendance at designated company summits and other business-related events as needed.

Responsibilities

Document data, analytics, and research needs for highly complex projects with a student- and equity-centered perspective, working with peers, cross-functional partners, faculty staff, and leaders.
Translate user stories into technical requirements.
Build trust and strong relationships with cross-functional partners and senior stakeholders.
Answer complex business questions that require knowledge of data assets across multiple domains and departments.
Identify appropriate data sources and datasets to evaluate hypotheses and produce forecasts.
Collaborate with Data Engineering to develop complex ETL/ELT processes and data pipelines.
Investigate and resolve complex data issues that affect accuracy, completeness, consistency, timeliness, and validity.
Collaborate with Data Engineering and other data and analytics partners to define standards and best practices that improve data quality.
Combine analysis, visualization, and narrative to communicate information compellingly and prompt deliberate action.
Participate in defining data visualization standards and best practices and promote their adoption.
Communicate effectively with peers, partners, and senior leaders through written and verbal formats, including email, presentations, meetings, and workshops.
Organize and document processes, projects, operations, data assets, and analytical and research insights so they are accessible and support organizational knowledge and efficiency.
Write and interpret technical documentation, including entity-relationship and conceptual, logical, and physical data models.
Contribute to data management platforms such as data dictionaries and catalogs.
Support the development of other team members through constructive feedback and sharing technical and institutional knowledge.
Drive tasks, activities, and medium-scale projects autonomously and collaboratively; track progress, dependencies, and challenges; break down complex goals; and support project planning.
Develop skills and knowledge, stay abreast of innovations, and contribute to deploying relevant innovations at the university.
Support leadership in strategic planning and contribute to departmental operational excellence.
Follow policies and methods for responsible, secure, and compliant data access, use, transformation, storage, and deletion; identify data security risks and take appropriate mitigation actions.
Perform other job-related duties as assigned.