Digital Analytics Engineer II

If you’re passionate about building a better future for individuals, communities, and our country—and you’re committed to working hard to play your part in building that future—consider WGU as the next step in your career.

Driven by a mission to expand access to higher education through online, competency-based degree programs, WGU is also committed to being a great place to work for a diverse workforce of student-focused professionals. The university has pioneered a new way to learn in the 21st century, one that has received praise from academic, industry, government, and media leaders. Whatever your role, working for WGU gives you a part to play in helping students graduate, creating a better tomorrow for themselves and their families.

The salary range for this position takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

At WGU, it is not typical for an individual to be hired at or near the top of the range for their position, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is:
 

Grade: Technical 405

Pay Range: $87,200.00 - $130,800.00

Job Description

The Digital Analytics Engineer (DAE) II supports the comprehensive design, development, implementation, and successful execution of digital behavioral analytics processes and data collection systems. As they advance their engineering career, DAEs are assigned increasing responsibilities in administrating one or more processes or systems in the analytics architectural ecosystem, overseeing business requirement discovery and development, interacting with systems and data architectures, and mentoring other DAEs.

The DAE II role requires increasing mastery of each phase of process/system development and a strong working knowledge of the fundamental education technology and IT systems used to analyze an end-to-end student journey. DAE IIs establish and maintain strong relationships with peers and leaders across IAR, Data Engineering, Product Management, EdTech, and assigned departments (e.g., Marketing, Enrollment, and Regional Operations). As technical solution engineers, DAE IIs participate in cross-functional initiatives, projects, and programs providing technical guidance and building analytics solutions designed to increase student engagement, success, and outcomes.

Job Duties

• Documents data and analytics needs in projects of high complexity with a student and equity-centered lens, collaborating with peers, cross-functional partners, faculty, staff, and leaders. Translates user stories into technical requirements.
• Designs medium-scale solutions and collaborates effectively with other technical specialists (e.g., data engineers) in the construction of data products, systems, and applications.
• Designs, tests, deploys, monitors, and maintains the primary analytics codebase for digital experiences.
• Sets and manages expectations about analytics tasks and activities through clear, timely and effective communication with partners and stakeholders.
• Identifies, investigates, and solves complex data issues, contributing to the accuracy, completeness, consistency, timeliness, and validity of the university’s data. Collaborates with Data Engineering and other data & analytics partners to define standards and best practices that increase data quality across the university.
• Supports and accelerates other team members’ development through constructive feedback and sharing of technical and institutional knowledge.
• Conveys information effectively to peers, partners, and senior leaders, using a variety of resources and formats (synchronous and asynchronous, verbal and written) such as e-mails, presentations, meetings, and workshops.
• Creates and organizes information about processes, projects, operations, data assets, and insights from analyses, making it accessible in ways that increase the university’s knowledge and efficiency. Writes and interprets technical documentation (e.g., Entity-Relationship, Conceptual, Logical, and Physical data models). Contributes actively to the enrichment of the university’s data management platforms (e.g., data dictionaries, catalogs, etc.).
• Drives tasks, activities, and small-scale projects with high levels of autonomy, confidence, and collaboration with peers and partners.
• Tracks and reports own progress, dependencies, and challenges diligently. Breaks down complex goals into concrete tasks and activities.
• Works actively in improving own skills and knowledge through internal and external, formal and informal, st