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.