Senior Data Engineer - Data Science Platform

Join the team responsible for powering the data and machine learning capabilities behind millions of customer experiences at ASOS. As part of the Data Science Platform group within Nishantha's organisation, you will help build and evolve the core data infrastructure that enables Data Scientists, ML Engineers and Analysts across Forecasting, Recommendations, Pricing, Marketing and Customer domains to develop, deploy and operate data-driven products at scale. This is an opportunity to work on a modern Azure-based data platform, solving large-scale data engineering challenges focused on scalability, reliability, performance and developer experience. Your work will directly support the delivery of machine learning and analytics capabilities across ASOS. What you’ll be doing - Designing and building data platform capabilities that support data and machine learning workloads across ASOS. - Developing high-performance data pipelines and processing frameworks using Python, Scala, Spark and Databricks. - Owning and evolving platform components that help engineers and data scientists build, test, deploy and monitor data products. - Improving platform reliability, observability, data quality and operational excellence. - Creating reusable libraries, tooling and engineering patterns that enable teams to deliver data products more efficiently. - Partnering with Data Scientists, ML Engineers and Product Engineering teams to solve data challenges and enable new machine learning use cases. - Contributing to architectural decisions and the evolution of data engineering standards across the organisation. - Optimising distributed workloads for performance, scalability and cost efficiency across the Azure ecosystem. - Supporting the long-term development of ASOS's data platform and engineering practices. - Working with multiple Data Science and Machine Learning teams across ASOS to deliver platform capabilities that create business value. We're interested in people who can demonstrate many of the following capabilities. If your experience does not match every requirement exactly, we still encourage you to apply. You are likely to have: - Experience building or operating large-scale data platforms or data-intensive applications in a cloud environment. - Experience working with Databricks, Spark and distributed data processing technologies. - Experience developing production-grade data engineering solutions using Python and/or Scala. - Experience designing data architectures that balance scalability, reliability and cost efficiency. - Experience implementing modern engineering practices, including CI/CD, automated testing, observability and Infrastructure as Code. - Demonstrated ability to solve complex engineering problems and improve platform capabilities that help other teams work more effectively. - Experience leading the design and delivery of complex data engineering solutions and contributing to technical direction and engineering best practices. - Experience mentoring engineers through technical guidance, code reviews and knowledge sharing. - Ability to collaborate effectively across teams and stakeholders, balancing business priorities with technical excellence to deliver scalable, reliable and maintainable data solutions.