Senior Data Engineer

Overview

As a Senior Data Engineer in ASOS’s Customer & Marketing Machine Learning team, you will build the data foundations powering ML models, pricing, and analytics at scale. You’ll work with data, ML engineers and scientists to deliver end-to-end ML products that impact marketing, pricing and customer experiences. You’ll design robust data pipelines and architectures, improving data quality and observability while enabling cross-functional decision making. This role offers the chance to influence ASOS’s data capabilities and support millions of customers globally.

Pay / Benefits

• Employee discount
• Employee sample sales
• 25 days paid annual leave
• Discretionary bonus scheme
• Private medical care
• Flexible benefits allowance

Responsibilities

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

Key requirements

• Significant experience delivering data engineering solutions in cloud environments
• Strong Python expertise with 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 modeling and modern data engineering principles
• Experience enabling data science, analytics or ML workloads through robust data infrastructure
• Strong understanding of CI/CD, Infrastructure as Code, automated testing and observability
• Experience working with large-scale customer, marketing, commercial or behavioural datasets
• Proven ability to lead design and delivery of complex technical solutions from concept to production
• Experience mentoring engineers and shaping technical direction within a team
• Strong stakeholder management and communication skills with technical and non-technical audiences
• A passion for solving challenging data problems to enable better decision-making
• Experience supporting ML platforms, MLOps or model operationalisation
• Experience with pricing, marketing analytics, recommendation systems or customer analytics
• Experience in ecommerce, retail or consumer-facing digital businesses

• Collaborative mindset
• Strong communication
• Mentorship and coaching
• Python
• Spark
• Databricks

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