Senior Data Engineer

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 

Join the team responsible for building the data and machine learning products that power customer experiences, marketing effectiveness and commercial decision-making across ASOS.

As a Senior Data Engineer in our Customer & Marketing Machine Learning team, you will play a key role in developing the data foundations that enable machine learning models, pricing optimisation, customer analytics, media measurement and marketing decisioning at scale. The team brings together Data Engineers, Machine Learning Engineers and Applied Scientists to deliver end-to-end machine learning products that create measurable business impact.

This is an opportunity to work with large-scale customer, marketing and commercial datasets, building robust data solutions that help transform how ASOS understands, engages and serves millions of customers.

• Designing and building scalable data pipelines that support machine learning, analytics and data science initiatives.
• Developing high-performance data solutions using Python, Spark, Databricks and Azure technologies.
• Creating and maintaining datasets that power customer, marketing, pricing and forecasting use cases.
• Collaborating closely with Applied Scientists and Machine Learning Engineers to operationalise machine learning models.
• Designing data models and architectures that enable reliable, trusted and accessible data across the business.
• Improving data quality, observability, lineage and monitoring capabilities across critical data products.
• Supporting the delivery of media measurement, customer value, pricing and personalisation initiatives.
• Optimising data processing workloads for performance, scalability and cost efficiency.
• Driving best practices across software engineering, data engineering and platform development.
• Providing technical leadership through design reviews, mentoring and knowledge sharing.
• Working with stakeholders across Customer, Marketing and Commercial functions to turn business challenges into scalable data solutions.
• Contributing to the long-term evolution of ASOS's machine learning and data capabilities.

We're interested in people who can demonstrate many of the following capabilities. If your experience doesn't match every requirement exactly, we still encourage you to apply.

• Significant experience delivering data engineering solutions within cloud-based environments.
• Strong expertise in Python and experience developing production-grade data pipelines and data products.
• Experience working with Databricks, Spark and distributed processing technologies.
• Experience designing and operating large-scale data platforms using Azure, AWS or GCP.
• Deep understanding of data modelling, data architecture and modern data engineering principles.
• Experience enabling data science, analytics or machine learning workloads through robust data infrastructure.
• Strong understanding of CI/CD, Infrastructure as Code, automated testing and observability practices.
• Experience working with large-scale customer, marketing, commercial or behavioural datasets.
• Proven ability to lead the design and delivery of complex technical solutions from concept through to production.
• Experience mentoring engineers and helping shape technical direction within a team.
• Strong stakeholder management and communication skills, with the ability to partner effectively with technical and non-technical audiences.
• A passion for solving challenging data problems and enabling teams to make better decisions through data.Experience supporting machine learning platforms, MLOps or model operationalisation.
• Experience with pricing, marketing analytics, recommendation systems or customer analytics.
• Experience working in eCommerce, retail or consumer-facing digital businesses.