Senior Data Engineer at ASOS

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

02 Jun, 26

Salary

0.0

Posted On

04 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, Azure Databricks, Azure Data Factory, Spark, PySpark, CI/CD, Azure DevOps, GitHub Actions, Terraform, Bicep, Data Governance, Data Modeling, ETL/ELT, Infrastructure as Code, Delta Lake

Industry

Retail Apparel and Fashion

Description

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 Shape the future of fashion through data. At ASOS, data isn’t just numbers, it’s the heartbeat of our business. With millions of customers worldwide and billions of interactions every year, we’re building one of the most advanced data platforms in eCommerce. This is your chance to work at the intersection of fashion and technology, designing solutions that power personalised experiences, optimise global operations, and unlock insights at scale. You’ll be part of a team that’s transforming how ASOS uses data to innovate faster, predict trends, and deliver the ultimate shopping experience. What You’ll Be Doing: Designing and developing large-scale, high-performance data pipelines for batch and real-time processing. Leveraging Azure services (Data Factory, Event Hubs, Service Bus) and Databricks to orchestrate complex workflows. Building robust ingestion and transformation frameworks using Spark/PySpark and Python, ensuring data quality and reliability. Implementing CI/CD pipelines for automated deployment and testing with tools like Azure DevOps and GitHub Actions. Collaborating in an agile, cross-functional team, working closely with data scientists, engineers, and product stakeholders. Driving best practices in data architecture, security, and infrastructure-as-code (Terraform/Bicep). Qualifications About You: Proven experience as a Data Engineer in cloud-native environments. Strong programming skills in Python (and ideally Scala) plus solid SQL knowledge. Hands-on expertise with Azure Databricks, Azure Data Factory, and Spark. Understanding of data modelling, ETL/ELT patterns, and distributed computing. Experience with CI/CD workflows, version control (Git), and testing frameworks (pytest, ScalaTest). Knowledge of open table formats (Delta, Iceberg, Apache Hudi). Familiarity with Infrastructure as Code tools (Terraform or Bicep). Proven implementation experience in data governance principles, including data catalogs, lineage, security, and data quality management Experience or familiarity with Agentic AI concepts or agent-based AI solutions is considered an advantage. 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

Responsibilities

The role involves designing and developing large-scale, high-performance data pipelines for both batch and real-time processing using Azure services and Databricks. Responsibilities include building robust ingestion and transformation frameworks with Spark/PySpark and Python, and implementing CI/CD pipelines for automated deployment.