Senior Data Engineer
Age of Learning • USPython Remote
Company Overview:
Age of Learning® is the leading developer of engaging and effective Pre-K through 5th grade learning resources that help children build a strong foundation for academic success and a lifelong love of learning. The company’s research-based curriculum, developed by education experts, includes the award-winning programs ABCmouse.com® Early Learning Academy and Adventure Academy™, as well as the adaptive, personalized school solutions, My Math Academy®, My Reading Academy®, and My Reading Academy Español. Having served over 50 million children worldwide, Age of Learning is a global leader in efforts to advance equity, access, and opportunity for all children. To learn more about Age of Learning, visit www.AgeofLearning.com.
Summary:
As a Senior Data Engineer on the Analytics team, you’ll help shape the architecture and long-term direction of our data platform while building and maintaining reliable, scalable data systems that power decision-making across the company. You’ll partner closely with data analysts, product managers, designers, and engineering teams to translate business and product needs into durable technical solutions. In this role, you’ll also mentor teammates, champion data quality and best practices, and help elevate the overall maturity and impact of our data organization.
Responsibilities:
• Design, build, and maintain a simple, effective, and scalable data warehouse on Snowflake — with clean models, well-named fields, and documentation that makes the warehouse easy to use by downstream users and systems
• Implement and manage data transformation with dbt to ensure reliable, well-tested pipelines
• Develop and evolve data models, semantic layers, and metric definitions that support a wide range of business needs while keeping data consistent and accurate across the organization
• Own data quality, observability, and testing that protects downstream consumers from broken or misleading data
• Build and evolve internal AI tooling (skills, agents, etc) that makes the Data Engineering team more effective
• Partner with analysts, product engineers, and business stakeholders to understand their needs, scope the right solution, and deliver outcomes
• Mentor analysts and peers, fostering a culture of learning, rigor, and continuous improvement
• Proactively identify operational issues and propose evolutionary solutions
• Implement and manage data transformation with dbt to ensure reliable, well-tested pipelines
• Develop and evolve data models, semantic layers, and metric definitions that support a wide range of business needs while keeping data consistent and accurate across the organization
• Own data quality, observability, and testing that protects downstream consumers from broken or misleading data
• Build and evolve internal AI tooling (skills, agents, etc) that makes the Data Engineering team more effective
• Partner with analysts, product engineers, and business stakeholders to understand their needs, scope the right solution, and deliver outcomes
• Mentor analysts and peers, fostering a culture of learning, rigor, and continuous improvement
• Proactively identify operational issues and propose evolutionary solutions
Minimum Qualifications:
• 5+ years of data engineering experience, with a track record of owning systems end-to-end
• Strong SQL, Python, and data modeling skills — opinionated about design strategies and best practices
• Hands-on experience with dbt and Snowflake
• Experience with clickstream / event data
• Demonstrated ability to design and ship scalable data systems
• Comfort using AI tools (Claude Code, Cursor, or similar) as part of your daily workflow
• Excellent written communication — clear documentation, well-scoped specs, and the ability to explain technical tradeoffs to non-technical partners
• Strong project ownership: defining requirements as you go, communicating tradeoffs, and delivering results within timelines
• Ability to leverage abstraction to solve complex problems
Preferred Qualifications
• Experience designing semantic layers, metric stores, or data contracts
• Experience building A/B testing or experimentation frameworks
• Experience building or contributing to internal AI tooling — skills, agents
• Strong SQL, Python, and data modeling skills — opinionated about design strategies and best practices
• Hands-on experience with dbt and Snowflake
• Experience with clickstream / event data
• Demonstrated ability to design and ship scalable data systems
• Comfort using AI tools (Claude Code, Cursor, or similar) as part of your daily workflow
• Excellent written communication — clear documentation, well-scoped specs, and the ability to explain technical tradeoffs to non-technical partners
• Strong project ownership: defining requirements as you go, communicating tradeoffs, and delivering results within timelines
• Ability to leverage abstraction to solve complex problems
Preferred Qualifications
• Experience designing semantic layers, metric stores, or data contracts
• Experience building A/B testing or experimentation frameworks
• Experience building or contributing to internal AI tooling — skills, agents