Senior Quality 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 As a Senior Quality Engineer - Data, you will play a pivotal role in elevating our quality practices across data products, analytics workflows, and complex distributed systems. You will be an expert within our engineering organization, deeply understanding product behaviour, source-to-consumption data flows, analytics use cases, and the systems that transform operational data into trusted customer and business insight. This role will balance hands-on individual contributor responsibilities with leading, influencing, and coaching your peers. This senior individual contributor role is for someone who is passionate about seeing systems holistically, has a strong vision for data quality, and is eager to drive the highest standards of accuracy, completeness, reliability, performance, and analytical trust. You will leverage your deep understanding of data platforms, data pipelines, databases, reporting layers, and complex system integrations to guide and influence our development process. Your role is not to manage a team, but to be a quality champion who partners directly with developers, data engineers, analytics engineers, product managers, and analysts. You will help teams anticipate risk, validate business logic, protect data integrity, and build more robust, scalable, and reliable data-enabled products. At the core of this role is a strong focus on the customer experience; success means our platform produces accurate, explainable, timely, and useful data that helps customers and internal teams make confident decisions. What You Will Own Own and drive end-to-end testing strategy for complex distributed systems, data pipelines, analytics workflows, and reporting experiences, proactively identifying risks, integration challenges, data quality gaps, and performance bottlenecks while establishing a clear quality vision across the product. Define and champion data quality standards for accuracy, completeness, consistency, freshness, uniqueness, validity, lineage, reconciliation, and analytical correctness across operational systems, data stores, transformations, APIs, and dashboards. Design and execute validation strategies for source-to-target data flows, including ingestion, transformation, business rules, aggregations, joins, schema changes, data contracts, exports, and downstream analytics consumption. Partner with Product, Design, Engineering, Data, and Analytics teams from ideation through delivery to ensure metrics definitions, acceptance criteria, test data, edge cases, and quality gates reflect the real business meaning of the data. Provide quality-focused input on testability, scalability, observability, and reliability during ticket grooming and feature discussions, offering insights on product resilience, data integrity, usability, and analytics trust. Build pragmatic automated checks and test frameworks for database validation, API validation, data reconciliation, pipeline regression testing, and analytics verification using common data and quality tools. Design and execute integration testing and performance testing for distributed systems and data-heavy workflows, including validation of batch, streaming, event-driven, and near-real-time data processing where applicable. Champion shift-left quality culture by mentoring developers, data engineers, and analytics partners on testing principles, data contracts, clear acce…