We’re Enroly - an award-winning EdTech company who are innovative, fast-paced, and scaling rapidly. We’re looking for a hands-on Data Engineer to join our Engineering team and lead on the most exciting data project in global higher education.
Our Data and Insights product offers ground-breaking, real-time business reporting to universities. It is a product upgrade on top of our industry-leading SaaS platform CAS Shield.
Enroly Data and Insights aggregates and anonymises real-time data, providing our clients with internal and industry comparison data, offering a resource akin to the ‘Bloomberg for higher education’. The product is live, and is actively used by a wide range of our UK university clients.
The solution has been developed cloud-first on an AWS Postgres Data Lake, and you will be collaborating closely with a talented team of front end developers and product managers, building out the queries to drive flexible and user friendly data visualisations.
The successful candidate will have the opportunity to shape the future of a flagship product, as we bring our current partner-developed data insights product in-house.
Essential experience:
Desirable but not mandatory experience:
Home office budget (to kit yourself out)
Private Health Insurance with online Doctor access
Private life insurance
Cycle to work (salary sacrifice your new bike)
Professional development budget
Lunch on us the last Friday of the month
4x away days per year and more!
Enroly is an investment-backed startup founded in late 2017 and the leading provider of enterprise automation software for UK universities.
In 2021 Enroly won the EdTechX Start-up of the Year Award. In 2020 the company won the prestigious “Enrolment Management Solution of the Year” at the Tech Breakthrough Awards. Enroly has fast become the industry leader with HE clients in the public and private university sector.
CAS Shield is a 100% proprietary, workflow automation tool, designed specifically for international student recruitment conversion and compliance.
CAS Shield automates close to 90% of the fatiguing and repetitive tasks faced by university staff. This includes: information and document requests, machine learning analysis of data/documents, screening for non-genuine students, and flagging students with low confidence for intervention.
The result is that university staff have more time for the qualitative aspect of student recruitment; providing human to human support to students that need it most.