About the Role
Data is a key priority for ASOS, and our Data Lakehouse, the ASOS Data Ecosystem (ADE), sits at the centre of how we turn data into insight and action.
This Associate Analytics Engineering role is designed for someone at the beginning of their career. You may be a recent graduate, a career changer, or someone with less than two years of relevant experience.
You'll join a team made up primarily of Data Engineers and, over time, develop into a role that helps connect engineering, stakeholders and product management.
Your initial focus will be hands-on work with data in ADE. You'll help explore, analyse and curate trusted analytical datasets built on top of the pipelines delivered by our Data Engineers. You'll work closely with experienced team members through pairing, mentoring and code review, taking on increasing ownership as your confidence and skills develop.
You'll also support stakeholder conversations and help our Product Manager understand business questions through analysis, evidence and clear documentation.
A significant part of the role involves experimentation and discovery. With support from the team, you'll analyse data, test assumptions, profile datasets and prototype solutions that help shape requirements and decision-making. As you develop, you'll start building analytical-quality data products using the same engineering standards applied across the team, including testing, version control and continuous integration practices.
This role will suit someone who enjoys both analytical problem-solving and working with people. You are curious, enjoy learning, ask thoughtful questions and can communicate findings clearly to technical and non-technical audiences alike.
You do not need to have experience with everything listed below. Training, support and mentoring will be provided, and we encourage applications from people with transferable skills and varied career journeys.
What You'll Be Doing
- Learn to design, build and maintain analytical data models and curated datasets in ADE (Databricks), transforming raw and core data into analysis-ready products.
- Work closely with Data Engineers, learning how the platform, pipelines and tooling fit together while gradually taking ownership of your own deliverables.
- Participate in stakeholder discussions to understand business challenges and help shape requirements through analysis, evidence and documentation.
- Carry out exploratory analysis and prototyping to test assumptions, profile source data and assess feasibility.
- Help evaluate and communicate the outcomes, adoption and business value of delivered solutions.
- Support the Product Manager with discovery activities and ad hoc business questions.
- Contribute to data quality through testing, validation and monitoring activities.
- Build analytical data products in dbt while learning analytics engineering best practices, including version control, testing, peer review and CI/CD.
- Document data models, business logic and workflows to support discoverability and self-service use of data.
- Enable downstream consumers, including Analysts, Data Scientists and BI Developers, to build reporting and insights on trusted, well-governed datasets.
About You
We're looking for someone with a strong interest in data and analytics, together with a willingness to learn and collaborate.
You may bring:
- A degree in a numerate, technical or analytical subject, or equivalent practical experience. We welcome applications from a variety of educational and career backgrounds.
- SQL skills, including the ability to write and understand queries, and an enthusiasm for continuing to develop those skills.
- Some exposure to Python, although this is not required.
- An interest in modern data platforms such as Databricks or Apache Spark and a willingness to learn them.
- An understanding of data modelling and data warehousing concepts such as tables, joins, facts and dimensions, gained through education, projects, placements or early-career experience.
- An interest in modern analytics development practices, such as version control, testing, peer review and deployment processes.
- Confidence to ask questions, seek clarification and use evidence to support your recommendations.
- An analytical mindset and the ability to explain findings in a clear and understandable way.
- Attention to detail and a commitment to producing accurate work.
- Strong collaboration and communication skills.
- An interest in cloud-based data platforms, particularly Azure.
Nice to Have
The following are beneficial but not required:
- Exposure to dbt.
- Experience building reports or dashboards using Power BI.
- Experience working in or alongside a product-led delivery team.
- Familiarity with agile ways of working.
- Exposure to orchestration tools such as Azure Data Factory, Airflow or Databricks Workflows.
- Awareness of Reverse ETL and data integration solutions such as Fivetran.
- Knowledge of DataOps practices.
- Experience in retail and/or e-commerce environments.
- Relevant coursework, personal projects or certifications related to analytics engineering or data engineering.
Support and Development
You'll receive:
- Structured onboarding covering ADE, team tools and business context.
- A buddy during your first months in the role.
- Regular one-to-one support from your manager.
- Ongoing pairing and code review with experienced Data Engineers.
- Dedicated learning time for training, certifications and conferences.
- A clear progression pathway towards an Analytics Engineer role.
- A supportive environment where questions are encouraged and learning is expected.
BeneFITS’
- 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