Director, Data & Analytics (Analytical Engineering)

Risepoint assists primarily regional universities in increasing their access and impact by making their academic programs available to students online. Founded in 2007, Risepoint's mission is to expand access to high-quality, affordable, and workforce-relevant education, especially for working and adult students. Risepoint brings single-minded dedication to student success, an integrated set of services, and data-driven performance to our collaboration with university partners.

Reporting to VP of Marketing Analytics, this role will be responsible for driving a transformative shift in how we model, serve, and scale trusted data across the organization. This is a critical role within our Marketing & Operations Strategy Analytics (MOSA) function. You will lead the development and adoption of a modern data stack, semantic layer standardization, and production-grade data products to support decision-making, reporting, and advanced analytics across the business. The ideal candidate is not just technically fluent, but also deeply invested in changing legacy ways of working, challenging the status quo, and building resilient, scalable foundations for the future of analytics.

Key Responsibilities

• Strategic Thinking: Define and lead the analytical engineering vision, strategy, and roadmap in alignment with business goals and measurable outcomes.
• Team Management: Build, mentor, and lead a high-performing, collaborative team of data/analytics engineers. Improve training and onboarding through curated internal guides and semantic layer education.
• Cross-Functional Collaboration: Partner with Data Science, Marketing Strategy, and Analytics Product teams to align on roadmap, data readiness, create usable, version-controlled, and documented data assets.
• Analytical & Communication Excellence: Translate complex, ambiguous analytical problems and data product needs into enterprise grade data models, and analytical datasets. Present recommendations to senior and executive stakeholders to influence high-level decisions.
• Data Governance and Strategy: Establish a centralized, governed source of truth for key business metrics (e.g., CPL, LTV, Conversion Rates, New Enrollments). Lead or participate in initiatives around definitional alignment, automated data quality checks, volume thresholds, schema validations, lineage tracking, and change alerts.
• Standards and Best Practices: Ensure data discoverability and knowledge-sharing through living documentation, dbt Docs, internal wikis, data dictionaries, lineage diagrams, and recipes.

What You’ll Need for Success

Education:

A bachelor’s degree in computer sciences, Engineering, or similar quantitative field.

Required Skills & Experience

• 8+ years in analytics/data engineering, with 2+ years leading or owning end-to-end data product development.
• Expert in SQL and ELT best practices using tools like dbt Cloud, Databricks, Python, and DataBricks.
• Experience with BI tools (e.g., Power BI) and designing semantic/metric layers for business users.
• Deep understanding of data modeling concepts (Kimball, star schema, wide tables).
• Experience with observability tools (e.g., Metaplane, dbt tests, Monte Carlo) and writing data quality rules.
• Strong communication skills and ability to influence across data, product, engineering, and business teams.
• A track record of delivering in ambiguous environments and scaling from legacy data environments to enterprise-grade maturity on modern data platforms.