{"schemaVersion":"jobsearcher.job.v1","id":"213caf4a57896c2df988056f","url":"https://jobsearcher.com/jobs/213caf4a57896c2df988056f","canonicalUrl":"https://jobsearcher.com/jobs/213caf4a57896c2df988056f","title":"Analytics Engineer/Data Engineer","description":"Education Analytics is a non-profit organization that strives to deliver sophisticated, research-informed analytics to educators and school administrators to support their work in improving student outcomes. The Data Engineering team enables this mission by ensuring that the data educators receive is accurate, up to date, secure, and easily accessible.\nLearn about EA\nConnect with EA! (https://www.linkedin.com/company/education-analytics/) Learn more about EA on our blog (https://www.edanalytics.org/blog) and our website (https://www.edanalytics.org/who-we-are).\nPosition Description\nWe are seeking a full-time Data Engineer or Analytics Engineer to join our team. The person in this role will lead the design, build, and maintenance of automated data pipelines and analytic systems. An ideal candidate has strong SQL skills, experience with data warehousing concepts, and familiarity with complex data integration. The Data Engineering team is responsible for extract/load processes, data warehouse design, data transformations, and data modeling. While we want our team members to have familiarity with all aspects of ELT, we welcome specialists who may be more experienced on either the data engineering or analytics engineering side. Our current stack uses an ELT approach via Apache Airflow and dbt to create data warehouses in Snowflake.\nOur team is working to change the education sector by building frameworks to enable collaboration across school systems. To do this, we use open data standards and open-source tools so that solutions we create can be used and re-used in different education agencies across the country. We build and maintain the Enable Data Union project (https://enabledataunion.org/) and open-source projects like Earthmover (https://github.com/edanalytics/earthmover). Our team's work includes building tools and creating and managing data systems using those tools.\nThese posts illustrate some projects that members of our team might work on:\nA Day in the Life of a Data Engineer at EA\nhttps://www.edanalytics.org/blog/day-in-the-life-q-a-with-senior-data-engineer-tom-reitz\nIntroducing Enable Data Union, an open framework for analytics and data warehousing with Ed-Fi data\nhttps://www.edanalytics.org/blog/introducing-enable-data-union-an-open-framework-for-analytics-and-data-warehousing-with-ed-fi-data\nTurning public data into custom insights: How EA has built a public data platform for our partners\nhttps://www.edanalytics.org/blog/turning-public-data-into-custom-insights-how-ea-has-built-a-public-data-platform-for-our-partners\nResponsibilities\nLead the design and implementation of data warehousing structures for research, analytics, and reporting/dashboarding\nApply best practices from software engineering to the development of ELT data pipelines\nImplement code testing, continuous integration, and deployment strategies to ensure system reliability\nStructure data in organized, intuitive ways applying data modeling techniques and practices\nDesign and implement complex pipelines to integrate data coming from a mix of APIs, flat files, or other database sources\nDevelop and improve internal tools and systems to empower our team to work more efficiently\nCollaborate within a team of analysts, school system leaders, and other engineers to create analytics solutions that are scalable and support research\nExplore and apply new cutting-edge tools to drive innovation across a variety of projects\nProactively identify and defend against potential data quality & processing issues\nQualifications\nExperience architecting data warehouse and data lake structures that are intuitive and performant\nKnowledge of best design practices in cloud-based data warehouses\nKnowledge of software engineering best practices, particularly in team-based development using Git\nExperience designing, implementing, and maintaining modern ELT pipelines\nFluency in SQL\nExperience with Python\nExperience with Linux\nBonus Skills:\nExperience with cloud-based columnar data warehouses and other cloud data technologies (Snowflake, RedShift, Databricks, MirageDB, Fabric, BigQuery)\nExperience with Data Build Tool (dbt)\nExperience with Apache Airflow or other modern data pipeline systems\nFamiliarity with AWS tooling and best practices\nHiring Process\nHiring team reviews resumes, cover letters, and application question responses.\nSelected candidates are invited to a 30-minute interview with two Data Engineering team members to discuss skills, experience alignment, and interests.\nSelected candidates are sent a technical skills exercise. Hiring team reviews exercise submissions.\nSelected candidates are invited for a full day final interview (virtual or in person in our downtown Madison office). 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.\nHow you will successfully onboard in this role\nFirst 30 days: Work through organizational and team onboarding. Get situated into Data Engineering team meetings and one on ones with your manager. Complete a training exercise our team has developed that familiarizes our new hires with our development setup and tooling.\nFirst 60 days: Begin to get involved in your first projects, familiarizing yourself with the project history, context, and goals by joining project meetings and connecting with teammates. Continue familiarizing yourself with our team's workflow processes and tools.\nFirst 90 days: Now fully integrated into your first projects, making regular code and documentation contributions. You may start sharing your development at our team meetings. We will start planning for you to take a lead role on sub-tasks within a project.\nAdditional details\nThe weekly expectation is 45 hours per week, and nights and weekends are sometimes required. Our preference is for candidates to primarily work from EA's office in Madison, WI. We are open to hiring a remote team member for the right candidate\nCompensation and Benefits\nThe salary for the Data Engineer (Analytics Engineer) position is $90,000-$120,000, based on experience. EA also has a generous benefits package including:\nA 12% employee salary contribution from EA to your 401k retirement plan\nAn additional 3% salary match by EA to your 401k\n26.5 days of paid vacation annually + sick paid time off that accumulates per pay period\n9 paid holidays of your choosing\n93% of health insurance premium paid for by EA\nPaid parental leave (if eligibility requirements are met)\nEA's primary location is in downtown Madison, WI, on the Capitol Square. Steps away from coffee shops, a weekly summer farmers' market, restaurants, shops, and two lakes. Many staff walk, bike, or use public transportation to commute to a well-appointed office.\nEqual Employment Opportunity\nEducation Analytics is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. (#_msoanchor_3)","company":"Education Analytics","rawCompany":"education analytics","city":"Madison","state":"WI","isRemote":false,"isActive":false,"createdAt":"2026-04-12T20:47:23.770Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Analytics Engineer/Data Engineer","description":"Education Analytics is a non-profit organization that strives to deliver sophisticated, research-informed analytics to educators and school administrators to support their work in improving student outcomes. The Data Engineering team enables this mission by ensuring that the data educators receive is accurate, up to date, secure, and easily accessible.\nLearn about EA\nConnect with EA! (https://www.linkedin.com/company/education-analytics/) Learn more about EA on our blog (https://www.edanalytics.org/blog) and our website (https://www.edanalytics.org/who-we-are).\nPosition Description\nWe are seeking a full-time Data Engineer or Analytics Engineer to join our team. The person in this role will lead the design, build, and maintenance of automated data pipelines and analytic systems. An ideal candidate has strong SQL skills, experience with data warehousing concepts, and familiarity with complex data integration. The Data Engineering team is responsible for extract/load processes, data warehouse design, data transformations, and data modeling. While we want our team members to have familiarity with all aspects of ELT, we welcome specialists who may be more experienced on either the data engineering or analytics engineering side. Our current stack uses an ELT approach via Apache Airflow and dbt to create data warehouses in Snowflake.\nOur team is working to change the education sector by building frameworks to enable collaboration across school systems. To do this, we use open data standards and open-source tools so that solutions we create can be used and re-used in different education agencies across the country. We build and maintain the Enable Data Union project (https://enabledataunion.org/) and open-source projects like Earthmover (https://github.com/edanalytics/earthmover). Our team's work includes building tools and creating and managing data systems using those tools.\nThese posts illustrate some projects that members of our team might work on:\nA Day in the Life of a Data Engineer at EA\nhttps://www.edanalytics.org/blog/day-in-the-life-q-a-with-senior-data-engineer-tom-reitz\nIntroducing Enable Data Union, an open framework for analytics and data warehousing with Ed-Fi data\nhttps://www.edanalytics.org/blog/introducing-enable-data-union-an-open-framework-for-analytics-and-data-warehousing-with-ed-fi-data\nTurning public data into custom insights: How EA has built a public data platform for our partners\nhttps://www.edanalytics.org/blog/turning-public-data-into-custom-insights-how-ea-has-built-a-public-data-platform-for-our-partners\nResponsibilities\nLead the design and implementation of data warehousing structures for research, analytics, and reporting/dashboarding\nApply best practices from software engineering to the development of ELT data pipelines\nImplement code testing, continuous integration, and deployment strategies to ensure system reliability\nStructure data in organized, intuitive ways applying data modeling techniques and practices\nDesign and implement complex pipelines to integrate data coming from a mix of APIs, flat files, or other database sources\nDevelop and improve internal tools and systems to empower our team to work more efficiently\nCollaborate within a team of analysts, school system leaders, and other engineers to create analytics solutions that are scalable and support research\nExplore and apply new cutting-edge tools to drive innovation across a variety of projects\nProactively identify and defend against potential data quality & processing issues\nQualifications\nExperience architecting data warehouse and data lake structures that are intuitive and performant\nKnowledge of best design practices in cloud-based data warehouses\nKnowledge of software engineering best practices, particularly in team-based development using Git\nExperience designing, implementing, and maintaining modern ELT pipelines\nFluency in SQL\nExperience with Python\nExperience with Linux\nBonus Skills:\nExperience with cloud-based columnar data warehouses and other cloud data technologies (Snowflake, RedShift, Databricks, MirageDB, Fabric, BigQuery)\nExperience with Data Build Tool (dbt)\nExperience with Apache Airflow or other modern data pipeline systems\nFamiliarity with AWS tooling and best practices\nHiring Process\nHiring team reviews resumes, cover letters, and application question responses.\nSelected candidates are invited to a 30-minute interview with two Data Engineering team members to discuss skills, experience alignment, and interests.\nSelected candidates are sent a technical skills exercise. Hiring team reviews exercise submissions.\nSelected candidates are invited for a full day final interview (virtual or in person in our downtown Madison office). 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.\nHow you will successfully onboard in this role\nFirst 30 days: Work through organizational and team onboarding. Get situated into Data Engineering team meetings and one on ones with your manager. Complete a training exercise our team has developed that familiarizes our new hires with our development setup and tooling.\nFirst 60 days: Begin to get involved in your first projects, familiarizing yourself with the project history, context, and goals by joining project meetings and connecting with teammates. Continue familiarizing yourself with our team's workflow processes and tools.\nFirst 90 days: Now fully integrated into your first projects, making regular code and documentation contributions. You may start sharing your development at our team meetings. We will start planning for you to take a lead role on sub-tasks within a project.\nAdditional details\nThe weekly expectation is 45 hours per week, and nights and weekends are sometimes required. Our preference is for candidates to primarily work from EA's office in Madison, WI. We are open to hiring a remote team member for the right candidate\nCompensation and Benefits\nThe salary for the Data Engineer (Analytics Engineer) position is $90,000-$120,000, based on experience. EA also has a generous benefits package including:\nA 12% employee salary contribution from EA to your 401k retirement plan\nAn additional 3% salary match by EA to your 401k\n26.5 days of paid vacation annually + sick paid time off that accumulates per pay period\n9 paid holidays of your choosing\n93% of health insurance premium paid for by EA\nPaid parental leave (if eligibility requirements are met)\nEA's primary location is in downtown Madison, WI, on the Capitol Square. Steps away from coffee shops, a weekly summer farmers' market, restaurants, shops, and two lakes. Many staff walk, bike, or use public transportation to commute to a well-appointed office.\nEqual Employment Opportunity\nEducation Analytics is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. (#_msoanchor_3)","datePosted":"2026-04-12T20:47:23.770Z","dateModified":"2026-04-12T20:47:23.770Z","hiringOrganization":{"@type":"Organization","name":"Education Analytics","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Madison","addressRegion":"WI","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"213caf4a57896c2df988056f"},"url":"https://jobsearcher.com/jobs/213caf4a57896c2df988056f"}}