Senior Data Engineer - Data Science/Machine Learning Platform

ASOS.com Ltd; Greater London; On-site; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Employee discount (ASOS discount)

Employee sample sales

25 days paid annual leave + extra day

Discretionary bonus scheme

Private medical care scheme

Flexible benefits allowance

Personalised learning opportunities

Job summary

ASOS.com Ltd in London is seeking a data platform engineer to help design and scale our Azure-based data platform supporting ML and analytics across forecasting, recommendations and pricing. You will build scalable data pipelines and evolving platform components to empower Data Scientists, ML Engineers and Analysts company-wide.

You will own reliability, observability and data quality, contributing to architectural decisions while collaborating with multiple data teams to deliver value at scale.

Qualifications

• Experience building data pipelines for ML/analytics.
• Strong background in distributed data processing and scalable architectures.
• Hands-on with Python/Scala for production-grade data engineering.
• Familiarity with Azure-based data platforms and cloud services.
• Experience implementing CI/CD, testing, observability and IaC practices.

Responsibilities

• 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.

Skills

Python

Scala

Apache Spark

Databricks

CI/CD

Infrastructure as Code

Azure

Observability

Tools

Databricks

Job description

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. 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.

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.

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