opengreenhousebaincapitalventures
Engineering Manager, Data Engineering
Rent the Runway
LocationGalway, Ireland
Last observed2026-06-24 08:29:18.873498
Job idbaincapitalventures-rent-the-runway:greenhouse:7867142
About Us: Rent the Runway (RTR) is transforming the way we get dressed by pioneering the world’s first Closet in the Cloud. Founded in 2009, RTR has disrupted the $2.4 trillion fashion industry by inspiring women with a more joyful, sustainable and financially-savvy way to feel their best every day. As the ultimate destination for circular fashion, the brand now offers infinite points of access to its shared closet via a fully customizable subscription to fashion, one-time rental or ownership. RTR offers designer apparel and accessories from hundreds of brand partners and has built in-house proprietary technology and a one-of-a-kind reverse logistics operation. RTR has been named to CNBC’s “Disruptor 50” five times in ten years, and has been placed on Fast Company’s Most Innovative Companies list multiple times. Galway Office Rent The Runway established its European Technology Hub in Galway in April 2019. Based in the historic Claddagh area of the city, the growing team in Galway tackles core technology challenges and influences the next generation of services critical to Rent The Runway’s success and continued growth. The Galway office is Rent the Runway's first international office outside the US and enables the company to significantly expand its Software Engineering, Product Development, Machine Learning Engineering and Data Science footprint. Rent The Runway’s Galway-based employees have the opportunity to grow their careers across several roles and career paths in Technology. Our engineering team is smart, pragmatic, and entrepreneurial. We practice continuous integration & test-driven development, engage in constant peer code reviews & pair programming, and work hard to give back to the software community through open-source contributions. About the Team The Data Engineering team plays a pivotal role in RTR’s technology and analytics ecosystem. The team is responsible for the data warehouse, data ingestion and transformation pipelines, and the infrastructure that enables reliable, high-quality data to flow across the company. The team partners closely with Data Science, Business Intelligence, Machine Learning, Product, Finance, Marketing, Operations, and Engineering teams to ensure RTR’s data platform is trusted, scalable, well-governed, and able to support critical business decisions. What You’ll Do As an Engineering Manager for Data Engineering at Rent the Runway, you will lead the team responsible for building, operating, and evolving RTR’s core data platform. You will combine strong engineering leadership with a deep understanding of data systems, data quality, platform reliability, and stakeholder needs. You will be responsible for leading a team of talented data engineers, setting technical direction, driving delivery of strategic data initiatives, and ensuring our data warehouse, pipelines, models, and data platform infrastructure are reliable, scalable, secure, and well-governed. This role is ideal for someone who enjoys building strong teams, partnering across technical and non-technical stakeholders, and leading data engineering work that has meaningful business impact. You will help shape how RTR captures, transforms, governs, and uses data across the organisation. Lead and develop a team of data engineers. Own delivery of key data engineering initiatives, from planning through execution. Drive the evolution of RTR’s data platform, including the data warehouse, pipelines, transformations, orchestration, and supporting infrastructure. Partner with Data Science, BI, ML, Product, Finance, Operations, and Engineering teams to deliver trusted data solutions. Set priorities for the team, balancing strategic work, stakeholder needs, operational support, and technical debt. Promote strong data quality, governance, documentation, lineage, and ownership practices. Help the team build reliable data pipelines using tools such as dbt, Python, Prefect, Airflow, or similar. Ensure data systems are observable, supportable, a
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