Data Engineer

We’re ASOS, the online retailer for fashion lovers all around the world.

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions.

But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.

Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.

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.

BeneFITS’

• Employee discount (hello ASOS discount!) 
• Employee sample sales 
• 25 days paid annual leave + an extra celebration day for a special moment 
• Discretionary bonus scheme 
• Private medical care scheme 
• Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits 
• Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role