Website Education Analytics

Education Analytics conducts research and develops rigorous anal

We are seeking a full-time Data Engineer or Analytics Engineer to lead the design, build, and maintenance of automated data pipelines and analytic systems. An ideal candidate has strong SQL skills and experience with data warehousing concepts, familiarity with complex data integration and/or analysis, and an interest in improving K-12 education.

This role supports the timely delivery of data and analytics to educators and administrators who use this data to drive change and improvement in education. We are looking for candidates who are innovative, hard-working, and curious to help us continue to develop our team’s capacity in the development and use of cutting-edge tools. Our team is consistently evaluating tools for new projects and looking for the best tools for the job. Our current stack uses an ELT approach via Apache Airflow and dbt to create data warehouses in Snowflake or Postgres, depending on the scale of the data. These posts illustrate some projects that members of our team might work on.


Lead the design and implementation of data warehousing structures for research, analytics, and reporting/dashboarding
Apply best practices from software engineering to data pipelines
Help implement code testing, continuous integration, and deployment strategies to ensure system reliability
Design and implement complex pipelines to integrate data coming from a mix of APIs, flat files, or other database sources
Develop and improve internal tools and systems to efficiently deliver high-quality, actionable metrics
Work collaboratively within a team of analysts, school system leaders, and other engineers to create analytics solutions that are scalable, easy to maintain, and support high quality research
Explore and apply new cutting-edge tools to drive innovation across a variety of projects


Experience architecting data warehouse and data lake structures that are intuitive and performant
Knowledge of best design practices in modern cloud-based data warehouses
Experience designing, implementing, and maintaining modern ELT pipelines with a clean code-base
Fluency in SQL, experience with Python and Linux.
Knowledge of software engineering best practices, particularly in team-based development using Git
Ability to proactively identify and defend against potential data quality & processing issues

Bonus Skills:

Experience with cloud-based columnar data warehouses (Snowflake, RedShift, BigQuery)
Experience with Data Build Tool (dbt)
Experience with Apache Airflow, or other modern data pipeline systems
Desire to work with cutting edge tools in a fast-paced environment
Familiarity with AWS tooling and best practices

Tell us about the interview process for this job

Hiring team reviews resumes and cover letters Selected candidates invited to 30-minute interview with Data Engineering team managers to discuss skills and experience alignment Selected candidates invited for full day final interview. Candidates are sent a skills exercise in advance that will be discussed in the interview. This doesn’t require any coding, it’s about concepts and planning of data systems, and doesn’t require any pre-submitted work. In addition to discussing the exercise, there will be another approximately 2-3 hours of interviews to meet other Data Engineering team members and key members of other teams and to help candidates learn more about Education Analytics & the role.

Tell us about your diversity and inclusion efforts

EA seeks to create a diverse team that reflects the people we serve. EA understands that diversity does not automatically facilitate inclusion, meaning that the organization actively works to promote a welcoming environment and foster a sense of belonging for staff of all identities through its policies and programs. EA seeks to eliminate disparities to industry entry and performance for those wishing to use their talents and skill in service to our mission. We recognize that staff enter with differing needs and that a workplace structured with difference in mind better serves all.

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