Senior Data Engineer - Data Science Platform

ASOS.com; Greater London; Hybrid; GBP 60,000 - 80,000; Full time

Benefits offered by this job

Employee discount

Private medical care

25 days paid annual leave

Job summary

ASOS.com is searching for a Senior Data Engineer to design and implement scalable data pipelines within their Azure ecosystem. The role involves working with Data Scientists and Engineers to optimize data workflows while mentoring teams on modern engineering practices. Candidates should have strong experience in Azure, Python, and data lifecycle management. Benefits include an employee discount, flexible benefits allowance, and 25 days paid annual leave, plus a special celebration day.

Qualifications

• Strong experience as a Data Engineer building scalable data platforms.
• Deep expertise in Azure (ADF, ADLS, Databricks).
• Proficiency in Python and/or Scala for large-scale data processing.

Responsibilities

• Designing, building, and maintaining scalable data pipelines.
• Developing and maintaining reusable data engineering templates.
• Driving standardisation and best practices across data ingestion.

Skills

Azure knowledge

Python

Scala

Data engineering best practices

CI/CD

Data modelling

Data quality

Tools

Databricks

Delta Lake

Terraform

dbt

Job description

Job Description

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