Key skills
Data EngineeringData ArchitectureDatabricksApache SparkLakehouse ArchitectureCloud Environments - AWSCloud Environments - AzureData ModelingDimensional ModelingSemantic LayersCI/CDInfrastructure as CodeAI/ML Data EnablementDelivery ExecutionStakeholder ManagementAIMLMLOpsAnalyticsSparkdbtAWSAzureLeadershipMentoring
About this role
Risepoint is an education technology company dedicated to increasing access to affordable education for working adults. As the Director of Data Engineering, you will lead the execution and delivery of scalable data products on Databricks, ensuring high performance and reliability while mentoring a team of data engineers.
Responsibilities:
- Lead, monitor and improve the end-to-end delivery of scalable data products and platform capabilities that enable high-quality insights, supporting Risepoint’s mission to expand access to affordable, workforce-relevant education
- Translate data platform priorities into actionable roadmaps, technical designs, and execution plans that drive measurable business value for university partners and learners
- Oversee the development of robust, efficient, and reliable data pipelines and lakehouse solutions on Databricks, ensuring performance, scalability, and cost optimization
- Guide and enforce enterprise data architecture standards, including data modeling, semantic layers, and reusable design patterns that support analytics, reporting, and AI/ML use cases
- Lead, mentor, and develop a team of data engineers, fostering a culture of accountability, continuous improvement, and innovation aligned to Risepoint’s values
- Provide hands-on technical leadership by reviewing designs, validating approaches, and supporting the team through complex engineering challenges
- Partner cross-functionally with product, analytics, and business teams to define, prioritize, and deliver data solutions that improve decision-making and enhance the student and partner experience
- Drive adoption of modern data engineering practices, including AI-assisted development, CI/CD, and infrastructure as code, to increase delivery speed and quality
- Enable AI and advanced analytics by ensuring data is well-structured, accessible, and model-ready, supporting initiatives that improve outcomes for students and institutions
- Manage multiple concurrent initiatives, balancing priorities, timelines, and resources while proactively communicating progress, risks, and dependencies to stakeholders
Requirements:
- 8–12 years of experience in data engineering, architecture, or software engineering, with strong hands-on expertise in Databricks, Apache Spark, and modern lakehouse architectures, as well as experience building scalable data pipelines in cloud environments (AWS and/or Azure)
- 3–5 years of experience leading data engineering teams and delivering complex, cross-functional data initiatives, with a proven ability to translate strategy into execution, manage priorities, and drive high-quality outcomes
- Strong foundation in data modeling (including dimensional modeling and semantic layers), along with experience in modern data practices such as CI/CD, infrastructure as code, and AI/ML data enablement
- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience)
- Experience leading teams through periods of change or transformation, including evolving business processes and leveraging modern technologies (such as AI-enabled tools) to improve efficiency, scalability, and business outcomes
- Familiarity with advanced Databricks capabilities and modern data ecosystem tools (e.g., Unity Catalog, Delta Live Tables, dbt, streaming technologies, or MLOps frameworks)
- Experience working closely with business stakeholders to define and deliver data products, particularly in environments that support analytics, reporting, or AI-driven decision-making