Digital Analytics Engineer

We’re looking for a Digital Analytics Engineer to help shape how ASOS understands customer behaviour across our digital estate.

This role sits at the heart of digital analytics and experimentation, combining analytics engineering, behavioural data modelling, and close partnership with product and engineering teams. You’ll ensure behavioural data is well designed, observable, and trusted, enabling teams to make confident decisions and run high quality experiments at scale.

Job Description

What You’ll Be Doing

Behavioural Data Modelling

Build and extend core behavioural models in Databricks that describe how customers interact with ASOS across web and app

Design and maintain:

Session logic

Funnels and journeys

Attribution logic

Feature usage and engagement metrics

Experiment exposure and variant datasets

Create domain specific behavioural marts optimised for analytics and experimentation use cases

Web Analytics Data Pipeline Ownership

Own the quality and consistency of behavioural events flowing into Analytics platforms

Ensure events conform to agreed:

Schemas and naming conventions

Data types and required fields

Privacy first compliance

Build and maintain transformation pipelines where enrichment or standardisation is required

Act as a technical owner of event contracts between frontend teams and analytics

Data Quality & Observability

In collaboration with the teams software engineers implement end-to-end data quality checks across frontend → ingestion → Analytics → Databricks

Monitor and alert on:

Schema changes and validation failures

Event completeness and coverage

Cardinality drift

Volume anomalies

Identity and user stitching integrity

Proactively identify and resolve issues before they impact experiments or reporting

Semantic Layer Enablement

Enable trusted behavioural metrics through:

Databricks metric enabled views

Power BI semantic models

Ensure metrics are usable for:

Self serve analysis

Executive and leadership reporting

“Talk to Data” and agent based workflows

Partner with product analysts, data and product teams to ensure metrics are clear, consistent, and reusable

Frontend Instrumentation Alignment

Work closely with web and app engineers to ensure instrumentation meets analytics and experimentation needs

Support:

Event payload and schema design

Instrumentation PR reviews

Pre‑release validation

Experiment tagging and exposure tracking

Act as a go to expert for behavioural tracking best practices

Qualifications

We’re Looking For

Core Skills & Experience

Experience in analytics engineering, data engineering, or product analytics

Strong SQL and experience working in Databricks / Spark / DBT/ Python

Solid understanding of behavioural and event based data modelling

Hands‑on experience with product analytics platforms (e.g. Mixpanel, Adobe or similar)

Experience building reliable data pipelines and quality controls

Comfortable working closely with software engineers within product teams on data instrumentation

A pragmatic, detail oriented approach to data quality

Nice to Have

Experience supporting experimentation and A/B testing

Knowledge of identity resolution and cross device tracking

Power BI semantic modelling experience

Experience enabling self serve analytics

Interest in AI assisted analytics or metric driven agents

Additional Information

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