Job 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.

Learn about EA  

Connect with EA! ( Learn more about EA on our blog ( and our website ( 

Position Description  

We 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.

Our 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 ( and open-source projects like Earthmover ( Our team's work includes building tools and creating and managing data systems using those tools.

These posts illustrate some projects that members of our team might work on:

• A Day in the Life of a Data Engineer at EA
• Introducing Enable Data Union, an open framework for analytics and data warehousing with Ed-Fi data
• Turning public data into custom insights: How EA has built a public data platform for our partners

Responsibilities

• Lead the design and implementation of data warehousing structures for research, analytics, and reporting/dashboarding
• Apply best practices from software engineering to the development of ELT data pipelines
• Implement code testing, continuous integration, and deployment strategies to ensure system reliability
• Structure data in organized, intuitive ways applying data modeling techniques and practices
• 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 empower our team to work more efficiently
• Collaborate within a team of analysts, school system leaders, and other engineers to create analytics solutions that are scalable and support research
• Explore and apply new cutting-edge tools to drive innovation across a variety of projects
• Proactively identify and defend against potential data quality & processing issues

Qualifications

• Experience architecting data warehouse and data lake structures that are intuitive and performant
• Knowledge of best design practices in cloud-based data warehouses
• Knowledge of software engineering best practices, particularly in team-based development using Git
• Experience designing, implementing, and maintaining modern ELT pipelines
• Fluency in SQL
• Experience with Python
• Experience with Linux

Bonus Skills:

• Experience with cloud-based columnar data warehouses and other cloud data technologies (Snowflake, RedShift, Databricks, MirageDB, Fabric, BigQuery)
• Experience with Data Build Tool (dbt)
• Experience with Apache Airflow or other modern data pipeline systems
• Familiarity with AWS tooling and best practices

Hiring Process

1. Hiring team reviews resumes, cover letters, and application question responses.
2. Selected candidates are invited to a 30-minute interview with two Data Engineering team members to discuss skills, experience alignment, and interests.
3. Selected candidates are sent a technical skills exercise. Hiring team reviews exercise submissions.
4. Selected 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.

How you will successfully onboard in this role

• First 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.
• First 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.
• First 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.

Additional details

The 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

Compensation and Benefits  

The salary for the Data Engineer (Analytics Engineer) position is $90,000-$120,000, based on experience. EA also has a generous benefits package including: 

• A 12% employee salary contribution from EA to your 401k retirement plan 
• An additional 3% salary match by EA to your 401k 
• 26.5 days of paid vacation annually + sick paid time off that accumulates per pay period
• 9 paid holidays of your choosing 
• 93% of health insurance premium paid for by EA 
• Paid parental leave (if eligibility requirements are met) 

EA'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.

Equal Employment Opportunity  

Education 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)

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