At a Glance
- Tasks: Design and implement scalable data pipelines using Python and Scala in an Azure ecosystem.
- Company: Join a leading fashion retailer with a focus on innovation and collaboration.
- Benefits: Enjoy employee discounts, flexible benefits, private medical care, and 25 days annual leave.
- Other info: Collaborative office culture with opportunities for personal growth and development.
- Why this job: Make a real impact by enhancing data accessibility and quality across diverse product teams.
- Qualifications: Strong experience in data engineering, Azure expertise, and proficiency in Python or Scala required.
The predicted salary is between 60000 - 80000 € 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 PySpark 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.
Qualifications
- Strong experience as a Data Engineer building scalable data platforms.
- Deep expertise in Azure (ADF, ADLS, Databricks).
- Proficiency in Python and/or Scala (PySpark/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.
Benefits
- Employee 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 plus an extra celebration day for a special moment.
- Employee sample sales.
Senior Data Engineer - Data Science Platform in London employer: ASOS.com
ASOS is an exceptional employer that fosters a collaborative and innovative work culture, particularly for the Senior Data Engineer role. With a strong emphasis on personal growth, employees benefit from tailored learning opportunities, flexible benefits, and a supportive environment that encourages teamwork and creativity. Located in a vibrant office setting, ASOS promotes a balanced work-life dynamic, ensuring that team members can thrive both professionally and personally.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - Data Science Platform in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the data engineering game. Building relationships can open doors that a CV just can’t.
✨Show Off Your Skills
Don’t just talk about your experience—show it! Create a portfolio of projects that highlight your data pipeline skills using Python, Scala, and Azure. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Ace the Interview
Prepare for those interviews by brushing up on common data engineering questions and scenarios. Be ready to discuss your past projects and how you’ve tackled challenges. Remember, it’s not just about the technical stuff; they want to see how you collaborate with teams too!
✨Apply Through Our Website
We love seeing applications come through our website! It shows you’re genuinely interested in joining us at StudySmarter. Plus, you’ll get to explore all the cool opportunities we have to offer while you’re at it!
We think you need these skills to ace Senior Data Engineer - Data Science Platform in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your expertise in Azure, Python, and Scala, and don’t forget to mention any experience with data pipelines and CI/CD practices.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how your background aligns with our mission at StudySmarter. Be sure to mention specific projects or achievements that showcase your skills.
Showcase Your Projects:If you’ve worked on relevant projects, whether in a professional setting or as personal endeavours, make sure to include them. We love seeing practical applications of your skills, especially those involving scalable data solutions and modern engineering practices.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values!
How to prepare for a job interview at ASOS.com
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Azure, Python, and Scala. Brush up on your knowledge of data pipelines, Spark, and Databricks, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've designed and implemented scalable data solutions. Think about challenges you faced and how you overcame them, particularly in relation to data quality and performance optimisation.
✨Understand the Business Context
Familiarise yourself with ASOS’s business model and how data engineering supports various product teams. Be ready to discuss how your work can enhance decision-making and improve data accessibility for stakeholders.
✨Emphasise Collaboration
Since the role involves working closely with Data Scientists and Engineers, be prepared to talk about your experience collaborating across teams. Highlight any instances where you’ve provided guidance or support to help others succeed in their data projects.
