Data Engineer
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About the Role
About StarRez
StarRez is the global leader in student housing software, providing innovative solutions for on and off-campus housing management, resident wellness and experience, and revenue generation. Trusted by 1,400+ clients across 25+ countries, StarRez supports more than 4 million beds annually with its user-friendly, all-in-one platform, delivering seamless experiences for students and administrators. With offices in the United States, Australia, the UK, and India, StarRez blends the robust capabilities of a global organization with the personalized care and service of a trusted partner.
The Role
You have an uncanny knack for problem solving and you have a sharp product mindset. Our engineers are involved in all aspects of the software design process and create high-performing, scalable, and secure products. You’ll work alongside cross-functional teams to design right-size solutions that power a new market-leading Analytics platform.
As a Data Engineer at StarRez, you will play a critical role in building and scaling the foundations of our Analytics & Data Platform. You’ll design and maintain reliable, secure, and scalable data pipelines and models that power a new generation of reporting, insights, and data-driven products across the StarRez ecosystem.
This role sits at the intersection of data, product, and engineering. You will work closely with Data Analysts, Full-Stack Engineers, and Product teams to translate customer and business requirements into robust data solutions - enabling everything from standardised dashboards to advanced analytics and embedded intelligence.
You are hands-on, pragmatic, and comfortable working in a fast-evolving environment where you’ll help shape both the technical platform and the operating model as we scale.
What you’ll be doing
- Build and maintain scalable data pipelines to ingest, transform, and model data for analytics and reporting
- Develop and optimise data models to support consistent dashboards and KPI definitions
- Ensure data quality and reliability through testing, monitoring, and observability practices
- Work with Data Analysts and Product teams to translate requirements into reusable datasets and pipelines
- Collaborate with Engineering to support data integration, schema automation, and platform scalability
- Integrate data from internal and external sources (APIs, third-party systems)
- Improve performance, scalability, and cost efficiency of the data platform
- Contribute to embedding analytics into the product (dashboards, reporting, data services)
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