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.
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
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
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