At a Glance
- Tasks: Design and implement scalable data pipelines using Python and Scala in an Azure ecosystem.
- Company: Join ASOS, a leading online fashion retailer with a vibrant culture.
- Benefits: Enjoy employee discounts, flexible benefits, private medical care, and 25 days annual leave.
- Other info: Embrace a dynamic work environment with opportunities for personal growth and creativity.
- Why this job: Make a real impact on data solutions while collaborating with diverse teams.
- Qualifications: Strong experience in data engineering, Azure, and proficiency in Python or Scala.
The predicted salary is between 63000 - 77000 £ per year.
As a Senior Data Engineer, you'll focus on designing and implementing scalable, reusable data pipelines, platform components, and data engineering standards that enable reliable, secure, and high-quality data solutions across the organisation.
You'll work closely with Data Scientists, Analysts, and Engineers embedded in product teams such as Forecasting, Recommendations, Marketing, Customer, and Pricing-helping them accelerate delivery and improve the quality and accessibility of data by providing a robust and standardised data platform experience.
- What you'll be doing
- Designing, building, and maintaining scalable data pipelines using Python and Scala, leveraging Spark and Py Spark within an Azure ecosystem (including Azure Data Factory and Databricks).
- Developing and maintaining reusable data engineering templates, frameworks, and tooling to support data teams across ASOS.
- Driving standardisation and best practices across data ingestion, transformation, and serving layers to ensure consistency across diverse product domains.
- Enabling teams to deliver high-quality, production-ready datasets by providing guidance, patterns, and hands‑on technical support.
- Implementing and promoting modern data engineering practices - including CI/CD for data pipelines, data quality validation, testing, observability, and metadata management.
- Collaborating with stakeholders to understand data requirements and evolving the data platform to meet business needs.
- Partnering with Platform Engineering, ML Engineering, and Security teams to ensure scalable, cost-efficient, and secure data infrastructure on Azure.
- Optimising data workflows and pipelines for performance, reliability, and cost efficiency.
We believe being together in person helps us move faster, connect more deeply, and achieve more as a team.
That's why our approach to working together includes spending at least 2 days a week in the office.
It's a rhythm that speeds up decision‑making, helps ASOSers learn from each other more quickly, and builds the kind of culture where people can grow, create, and succeed.
- Strong experience as a Data Engineer building scalable data platforms
- Deep expertise in Azure (ADF, ADLS, Databricks)
- Proficiency in Python and/or Scala(Py Spark/Spark) for large‑scale data processing
- Hands‑on experience with Databricks and Delta Lake
- Solid understanding of the end-to-end data lifecycle (ingestion transformation serving)
- Experience with dbt for transformations and Terraform for infrastructure as code
- Familiarity with CI/CD pipelines and modern data engineering best practices
- Strong grounding in data modelling, quality, and testing
- Experience with monitoring, observability, and performance optimisation
- Focus on automation, standardisation, and improving developer experience
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.
- Employee discount (hello ASOS discount!)
- Opportunity for personalised learning and in‑the‑moment experiences that enable you to thrive and excel in your role
- Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits
- Private medical care scheme
- Discretionary bonus scheme
- 25 days paid annual leave + an extra celebration day for a special moment
- Employee sample sales
- #J-18808-Ljbffr
Data Engineer - Data Science Platform in City of Westminster employer: We're Asos
Asos is an excellent employer, offering a dynamic work culture that fosters collaboration and innovation in the fashion industry. With a strong focus on employee growth, you will have access to professional development opportunities while enjoying benefits such as generous discounts, private medical care, and 25 days of annual leave. Located in a vibrant area, Asos provides a unique environment where creativity thrives and your contributions directly impact the brand's success.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Data Science Platform in City of Westminster
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like We're Asos!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer - Data Science Platform at We're Asos.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like We're Asos.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer - Data Science Platform at We're Asos, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer - Data Science Platform in City of Westminster
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 We're 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 We're 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 We're 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 We're 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.