Senior Data Engineer, Analytics

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.

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.

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.

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.

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  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.

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  Provide advanced data platform support across ingestion, transformation, orchestration, monitoring, and warehouse operations—ensuring dependable data delivery, strong performance, and efficient operations.

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  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.

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  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.

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  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.

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  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).

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  Implement secure-by-design practices across the platform, including least-privilege access patterns, secure sharing approaches, and support for privacy/compliance requirements.

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  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.

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  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.

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  Mentor and support other engineers, providing technical guidance, code reviews, and coaching on best practices to elevate overall team capability.

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  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.

• 5+ years of experience in data engineering, platform/data operations, or related roles, with demonstrated ownership of production pipelines and platform reliability.

• Advanced proficiency in SQL and strong experience diagnosing and resolving production data issues (e.g., ingestion failures, schema drift, data anomalies, performance bottlenecks).

• Hands-on experience with dbt or similar transformation frameworks to build and maintain data models within a cloud data warehouse, including testing, documentation, and modular design patterns.

• Experience supporting a modern cloud data warehouse; Snowflake experience is acceptable and preferred, including practical knowledge of object management, performance considerations, and access patterns.

• Experience operating ingestion tooling such as Fivetran (or similar managed ingestion tools) in a production environment, including troubleshooting and scaling ingestion workloads.

• Demonstrated experience implementing monitoring/alerting and operational processes that improve reliability, reduce MTTR, and increase data freshness consistency.

• Strong communication and collaboration skills, with the ability to partner effectively across technical and non-technical teams.

• Strong time management skills and ability to balance competing priorities.

• Commitment to excellence and a high level of integrity.
  

Bachelor’s degree in Computer Science, Engineering, Data Science, or a relative quantitative discipline.

Full-time

Remote

The expected base salary range for this position is $88,000-$97,000, however the offered salary may be higher or lower than the above range dependent on numerous factors including, but not limited to location, work experience, skills and internal equity considerations. The base salary is not inclusive of benefits or other incentives.

A cover letter and resume are required to be considered for this position.

New employees will be required to successfully complete a background check.

Any communication to applicants relating to the Great Minds hiring process will only come from email addresses with the domains greatminds.org or greatminds.recruitee.com. If in the course of the application or hiring process with Great Minds you are contacted through another domain, are requested to provide banking or other sensitive information, or you note any other suspicious activity, please contact security@greatminds.org

Great Minds is an equal opportunity employer. We will extend equal opportunity to all individuals without regard to race, religion, color, sex (including pregnancy, sexual orientation, and gender identity), national origin, disability, age, genetic information, or any other status protected under applicable federal, state, or local laws. Our policy reflects and affirms the organization’s commitment to the principles of fair employment and the elimination of all discriminatory practices.

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