Senior Data Engineer - Data Science/Machine Learning Platform

Posted 2 Days Ago
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London, England, GBR
Hybrid
Senior level
eCommerce • Retail
The Role
Designs and builds Azure-based data platform capabilities supporting large-scale data engineering, machine learning, and analytics workloads. Develops high-performance pipelines with Python, Scala, Spark, and Databricks; improves reliability, observability, data quality, scalability, and cost efficiency; creates reusable tooling and engineering standards; partners with data scientists and ML engineers; contributes to architecture, technical direction, mentoring, and platform practices.
Summary Generated by Built In
Company Description

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.

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.

Qualifications

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.

Additional Information

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 

Skills Required

  • Experience building or operating large-scale data platforms or data-intensive applications in a cloud environment
  • Experience with Databricks, Spark, and distributed data processing technologies
  • Production-grade data engineering experience using Python and/or Scala
  • Experience designing scalable, reliable, and cost-efficient data architectures
  • Experience with CI/CD, automated testing, observability, and Infrastructure as Code
  • Ability to solve complex engineering problems and improve platform capabilities
  • Experience leading complex data engineering solutions and contributing to technical direction
  • Experience mentoring engineers through technical guidance, code reviews, and knowledge sharing
  • Ability to collaborate across teams and stakeholders while balancing business and technical priorities

ASOS Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about ASOS and has not been reviewed or approved by ASOS.

  • Wellbeing & Lifestyle Benefits — Feedback suggests perks like a sizable, shareable product discount, access to sample sales, free gym access, and on-site amenities are valued. Such lifestyle-oriented benefits are frequently highlighted as standout aspects of the package.
  • Leave & Time Off Breadth — Feedback suggests employees benefit from substantial annual leave with bank holidays and an extra celebratory or birthday day off, with summer early finishes referenced in some contexts. This breadth of time-off options supports work-life balance.
  • Healthcare Strength — Feedback suggests access to a private medical care scheme is a core part of the package. This contributes to a perception of strong healthcare support.

ASOS Insights

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The Company
HQ: London
3,200 Employees
Year Founded: 2000

What We Do

We exist to give people 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 judgment, and channel your creativity into a platform used by millions. Whatever your role, asos will encourage you to be you, fulfilling your creative potential with our global reach. Push boundaries, and challenge expectations. We’re determined to succeed, so we’ll trust you to deliver. Help drive our journey to becoming the global fashion destination for 20-somethings At ASOS our 3,000+ employees are immersed in the creative worlds and have a truly entrepreneurial attitude. Our ASOSers are authentic, brave, creative and disciplined to the core and find ways to blend our passion for fashion with cutting edge technology. Sound up your street? Join us.

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