Senior Data Engineer

Overview

As Senior Data Engineer, you will build scalable data foundations powering ML models, pricing optimisation, and marketing analytics at ASOS. You’ll collaborate with data and ML teams to deliver end-to-end data products that impact customer experiences and business decisions. You’ll shape data architectures, ensure quality and observability, and drive scalable, cost-efficient data solutions. This role offers the chance to influence how millions of customers are understood and served through data-driven insights.

Pay / Benefits

• employee discount
• employee sample sales
• 25 days paid annual leave + extra day
• discretionary bonus
• private medical care
• flexible benefits allowance

Responsibilities

• Design and build scalable data pipelines for ML, analytics, and data science use cases
• Develop high-performance data solutions using Python, Spark, Databricks, and Azure
• Create and maintain datasets powering customer, marketing, pricing, and forecasting use cases
• Collaborate with Applied Scientists and ML Engineers to operationalise models
• Design data models and architectures for reliable, trusted data access across the business
• Improve data quality, observability, lineage, and monitoring of critical data products
• Support media measurement, customer value, pricing, and personalisation initiatives
• Optimise data processing workloads for performance, scale, and cost efficiency
• Drive best practices across software, data engineering, and platform development
• Provide technical leadership via design reviews, mentoring, and knowledge sharing
• Work with stakeholders across Customer, Marketing, and Commercial functions to translate business challenges into scalable data solutions
• Contribute to the long-term evolution of ASOS's ML and data capabilities

Key requirements

• Extensive experience delivering data engineering solutions in cloud environments
• Strong Python expertise and production‑grade data pipelines and data products
• Experience with Databricks, Spark, and distributed processing
• Experience designing and operating large-scale data platforms on Azure, AWS, or GCP
• Deep understanding of data modelling, architecture, and modern data engineering principles
• Experience enabling data science/analytics/ML workloads through robust data infrastructure
• Knowledge of CI/CD, Infrastructure as Code, automated testing, and observability
• Experience with large-scale customer/marketing/commercial/behavioural datasets
• Proven ability to lead design and delivery of complex technical solutions from concept to production
• Experience mentoring engineers and shaping technical direction
• Strong stakeholder management and communication skills with technical and non-technical audiences
• Passion for solving data problems and enabling data-driven decisions
• Experience supporting ML platforms, MLOps, or model operationalisation
• Experience with pricing, marketing analytics, recommendations, or customer analytics
• Experience in eCommerce, retail, or consumer-facing digital businesses

• stakeholder management
• communication
• mentoring
• Python
• Spark
• Databricks

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