At a Glance
- Tasks: Build and evolve a data platform that powers millions of users.
- Company: Join ASOS, the go-to online retailer for fashion enthusiasts worldwide.
- Benefits: Enjoy employee discounts, 25 days leave, private medical care, and more.
- Other info: Collaborative environment with opportunities for personal growth and learning.
- Why this job: Make a real impact in data science and AI while being your true self.
- Qualifications: Experience in data platforms and strong Python skills required.
The predicted salary is between 60000 - 75000 £ per year.
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.
Contribute to building and evolving the platform (infrastructure + reusable abstractions) that standardises data engineering workloads (batch/streaming pipelines, data processing) and traditional ML workflows (feature engineering, training, batch/real-time serving) across teams.
- Implement platform-level IaC, CI/CD, and environment management to support consistent, reproducible workloads across dev/test/prod.
- Build and maintain components using Python and Spark for data processing, shared datasets, and platform services.
- Contribute to shared services for data and ML lifecycle management (data pipelines, experiment tracking, versioning, lineage, permissions), aligned to enterprise governance (e.g. Unity Catalog).
- Support the implementation and operation of a centralised AgentOps capability (LLM gateway, tool integration, prompt and version management).
- Contribute to agent-specific lifecycle and safety controls (evaluation pipelines, guardrails, access control), with guidance from senior engineers.
- Enhance observability across both domains: Data & ML Ops: data quality, pipeline reliability, model performance; Agent Ops: traces, responses, evaluations, cost and behaviour monitoring.
- Contribute to problem solving across platform reliability, performance, and security for data, ML, and agent workloads.
- Apply security and compliance best practices (RBAC/ACLs, secure configuration, identity and access management), supporting a secure-by-default platform design.
- Collaborate with Data Engineers, Data Scientists, and ML Engineers to enable adoption of platform capabilities across ASOS Tech.
- Contribute to documentation, standards, and best practices across the platform.
Qualifications:
- Experience in Data Platforms, Data Engineering, Cloud Engineering, or ML Platform Engineering roles, with exposure to Azure.
- Strong hands-on experience with Python and Apache Spark.
- Experience with Azure data platform technologies such as Azure Databricks, ADLS Gen2, and Unity Catalog.
- Working knowledge of security and access management (RBAC, ACLs, identity concepts such as Entra ID).
- Familiarity with Infrastructure as Code using Terraform.
- Experience with CI/CD (Azure DevOps, GitHub Actions).
- Basic understanding of Azure networking (vNets, NSGs, Private Endpoints).
- Exposure to Docker/Kubernetes in cloud environments is beneficial.
- Awareness of AgentOps patterns (LLM gateways, prompt/version control, evaluation, observability) is a plus.
- Good communication and collaboration skills, with a strong focus on learning and continuous improvement.
Additional Information:
- Employee discount (hello ASOS discount!).
- Employee sample sales.
- 25 days paid annual leave + an extra celebration day for a special moment.
- Private medical care scheme.
- Fixed Annual Payment in addition to your salary each year, it's just an extra thank you from us.
- Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role.
Platform Engineer – Data Science & AI Platform in London employer: ASOS
ASOS is an excellent employer that fosters a dynamic and inclusive work culture, offering hybrid working arrangements that promote work-life balance. Employees benefit from generous perks such as 25 days of paid annual leave and exclusive discounts, while also having ample opportunities for professional growth in a fast-paced, technology-driven environment focused on innovation in payment processing.
StudySmarter Expert Advice🤫
We think this is how you could land Platform Engineer – Data Science & AI Platform in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Platform Engineer – Data Science & AI Platform in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at ASOS, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at ASOS. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at ASOS
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at ASOS!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.