Director of Data

Position Summary:At Penn Foster Group, our purpose is to open doors to brighter futures by helping learners gain the skills they need to grow their careers. Penn Foster Group is a mission-driven, PE-backed education company focused on helping learners gain the skills needed for long-term career success. As we scale toward 150,000 learner completions, we are investing in a modern data platform to support B2B partnerships, learner outcomes, and operational decision-making. Data is foundational to this transformation. We are seeking a Director of Data to lead and operate our data platform across Data Engineering, Self-Service Analytics, and MLOps. This role is responsible for executing the data strategy, ensuring reliable and scalable data systems, and enabling the business through trusted, governed, and accessible data. This role leads the execution and scaling of the data platform, translating strategic priorities into clear, predictable delivery across engineering teams. The data organization operates as a centralized platform team, delivering domain- aligned data products to the business. This role reports to the Senior Director, Product and Data Engineering and will lead a team of ~12–14 across Data Engineering, Analytics Engineering, and MLOps, including three technical leads. The ideal candidate brings strong leadership experience, deep understanding of modern data platforms (Databricks, Azure), and the ability to drive execution through technical leaders and teams. This role will oversee data governance, data quality, observability, and cost optimization to ensure platform reliability, scalability, and business impact.Essential Job Functions:Lead, mentor, and develop a team of data engineering leads, data engineers, and BI analysts, driving accountability, clarity, and delivery outcomes.Own day-to-day prioritization, execution, and delivery of the data platform within defined strategic prioritiesTranslate strategic direction into a clear, executable roadmap and ensure predictable delivery through strong operating cadence.Own and deliver data products aligned to business domains (e.g., Enrollments, Calls, Emails), ensuring they are reusable, governed, and trusted.Reduce reliance on ad-hoc reporting by scaling self-service data capabilities and enabling business teams to access data independently.Lead the execution and evolution of the data platform on Databricks and Azure, including migration away from legacy systems.Ensure high standards for data quality, reliability, freshness, and observability across pipelines and datasets.Establish and enforce platform-wide standards for data modeling, performance optimization, governance, and operational excellence.Define and enforce architectural guardrails across the platform, ensuring consistency, scalability, and alignment across domains.Partner with engineering, product, and analytics teams to ensure data systems are aligned to business needs and integrated into core workflows.Oversee and support MLOps capabilities, ensuring the platform supports scalable model deployment, monitoring, and lifecycle management.Establish and track SLAs for data availability, accuracy, and performance, improving overall trust in the data platform.Manage and optimize platform costs, including Databricks (DBU) usage and Azure infrastructure, driving efficiency and visibility.Build strong relationships with stakeholders across the organization, driving adoption of self-service data and surfacing gaps, risks, and opportunities.Identify team and capability gaps and support hiring for key roles, including Data Engineering Leads, Data Engineers, and BI Analysts.Knowledge, Skills, Abilities:8+ years of experience in data engineering, data platforms, or related fields3+ years of experience leading teams through managers or technical leadsProven experience building and operating modern data platforms (Databricks, Azure, or similar)Strong understanding of data modeling, pipeline development, and large-scale data systemsExperience with data governance, data quality, and observability practicesExperience enabling BI and self-service analytics environments (e.g., Power BI, Tableau)Proven ability to build or operate data platforms that enable scalable production ML systems, including model deployment, monitoring, and lifecycle management, in partnership with analytics and data science teamsDemonstrated success migrating from legacy data platforms to modern cloud-based architecturesProven ability to scale self-service data capabilities across business domainsStrong understanding of cloud cost management and optimization (e.g., Databricks DBU, Azure infrastructure)Demonstrated ability to drive execution, prioritize effectively, and deliver measurable outcomesStrong leadership skills with the ability to influence, coach, and elevate team performanceStrong communication skills with the ability to partner across technical and business teamsOccasional travel for in-person meetings will be required t