Data Engineer

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) Support advanced use cases such as forecasting, benchmarking, and data-driven insights Required Qualifications 3+ years of hands-on experience as a Data Engineer, building and maintaining reliable, scalable data pipelines and platforms Experience designing and maintaining ETL/ELT pipelines (batch and/or streaming) Experience with cloud data platforms (e.g., Snowflake, Azure Synapse, Microsoft Fabric or similar) including IAC Familiarity with modern data tooling (e.g., dbt, Airflow, Fivetran, Azure Data Factory or equivalents) Understanding of data integration patterns (APIs, ingestion pipelines, transformation layers) and Solid understanding of data modelling (star schema, dimensional modelling, data warehousing concepts) Knowledge of data quality, testing, and observability practices (monitoring, validation, lineage) Strong database fundamentals and SQL experience; comfortable designing safe schema changes considering performance optimisation, scalability, and cost management in data systems Ability to work closely with Data Analysts and stakeholders to translate requirements into scalable data solutions Strong communication skills with the ability to turn ambiguous requirements into structured data models and pipelines Pragmatic approach to balancing speed, quality, and scalability An inclination towards communication, inclusion, and visibility Preferred Qualifications Understanding of CI/CD pipelines and DevOps principles Experience working with multi-tenant SaaS data models and secure data access patterns (e