Role Snapshot
Lead delivery of reliable, scalable data pipelines and strengthen data platform support enabling trusted analytics and reporting across Great Minds. Own complex source integrations end-to-end, set engineering standards, and build curated datasets using dbt within Snowflake to support data-driven decision-making across the organization.
Job Description
Who We Are
Great Minds is a high-growth, mission-driven organization founded by educators in 2007. As a for-profit, Public Benefit Corporation, we believe all students deserve access to meaningful, challenging content—and all teachers deserve tools that are intuitive, effective, and built for the realities of today’s classrooms.
We develop high-quality, knowledge-rich math, science and ELA curricula grounded in research and designed in collaboration with educators. Our materials reflect real classroom needs and are built to drive lasting student outcomes.
We are committed to usability, coherence, and practical implementation—supporting teachers not just through curriculum, but with professional learning, purposeful technology, and responsive service that enable strong adoption and impact.
What We Build
Our products—Eureka Math and Eureka Math², Wit & Wisdom, PhD Science, Geodes, and the newly launched Arts & Letters ELA—are trusted by thousands of schools and districts nationwide.
Eureka Math is the most widely used math curriculum in the U.S., and is focused on balancing conceptual understanding, procedural fluency, and application.
Wit & Wisdom® and Arts & Letters ELA™ anchor our reading strategy with content-rich, grade-level instruction that integrates literature, history, and the arts, grounded in the science of reading. Geodes® complements our reading suite with decodable texts that pair phonics with meaningful content to support early literacy.
PhD Science is a hands-on K-5 Science program that sparks curiosity as students build enduring knowledge of how the scientific world works.
These programs reflect a shared belief in high expectations, joyful rigor, and deep respect for educators and students.
Where We’re Headed
Great Minds is entering a new stage of growth and product maturity. We are focused on building more connected, customer-informed experiences across the full educator journey—from curriculum to professional learning to platform and support.
Our long-term vision is to become a true partner in impact—not just delivering curriculum, but supporting educators in achieving outcomes at scale.
Job Purpose
Great Minds is seeking a hands-on Senior Data Engineer to lead delivery of reliable, scalable data pipelines and strengthen data platform support that enables trusted analytics and reporting across the organization. Our organization is dedicated to generating and using data to inform strategy and evaluate performance, supporting our mission to drive change from leadership all the way to the classroom. In this role, you will own complex source integrations end-to-end, set engineering standards that improve delivery speed and reliability, and build curated datasets using dbt (or similar) within our cloud data warehouse (including Snowflake). You will partner closely with analytics, data governance, and business stakeholders to deliver dependable data products, improve platform observability, and reduce operational burden through automation and best practices.
Responsibilities
Lead end-to-end delivery of complex pipelines and integrations, including new source onboarding, secure connectivity, ingestion configuration (primarily Fivetran), validation, production deployment, and operational handoff.
Provide advanced data platform support across ingestion, transformation, orchestration, monitoring, and warehouse operations—ensuring dependable data delivery, strong performance, and efficient operations.
Design and maintain dbt (or similar) models within the cloud data warehouse (including Snowflake) to transform raw data into curated, consumption-ready datasets with clear documentation and defined ownership.
Establish and promote engineering standards and patterns for pipeline development (naming conventions, load strategies, data contracts, error handling, testing, and documentation) to improve consistency and reduce time-to-data.
Own and improve pipeline reliability by implementing monitoring/alerting, defining operational SLAs/SLOs (freshness, success rate), leading incident response, and driving root-cause analysis and preventative fixes.
Improve platform performance and cost efficiency by analyzing workload/resource usage, identifying bottlenecks, and implementing optimizations (e.g., warehouse sizing strategies, job scheduling patterns, and query/pipeline performance tuning).
Implement secure-by-design practices across the platform, including least-privilege access patterns, secure sharing approaches, and support for privacy/compliance requirements.
Partner with data governance and analytics teams to enhance data quality and trust, implementing validation checks, reconciliation routines, freshness monitoring, and source-to-target documentation.
Support deployment and change management for pipelines and warehouse objects (version control, CI/CD patterns, environment promotions), and drive improvements to reduce manual release effort.
Mentor and support other engineers, providing technical guidance, code reviews, and coaching on best practices to elevate overall team capability.
Collaborate cross-functionally to translate business needs into well-scoped technical solutions, communicate tradeoffs clearly, and deliver high-impact enhancements to sources, pipelines, models, and platform capabilities.