ASOS
Retail
DigitalAnalyticsEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Digital Analytics Engineer at ASOS. Skills: Analytics engineering, Behavioural data modelling, Data quality, Experimentation. Build behavioural models. Extend behavioural models”
What You'll Achieve.
Enable confident decisions; Run high quality experiments
Industry & Context.
Identify issues; Resolve issues; Troubleshooting
What They're Looking For.
Must Have
Analytics engineering experience, Data engineering experience, Product analytics experience, SQL experience, Databricks experience, Spark experience, DBT experience, Python experience, Behavioural data modelling, Event based data modelling, Product analytics platforms experience, Reliable data pipelines, Data quality controls, Work with software engineers, Data instrumentation
Nice to Have
Experimentation experience, A/B testing experience, Identity resolution knowledge, Cross device tracking knowledge, Power BI semantic modelling, Self serve analytics enablement, AI assisted analytics interest, Metric driven agents interest
What You'll Do.
Build behavioural models
Extend behavioural models
Maintain session logic
Maintain funnel logic
Maintain journey logic
Design attribution logic
Maintain attribution logic
Design engagement metrics
Maintain engagement metrics
Design experiment datasets
Maintain experiment datasets
Create behavioural marts
Own data pipeline quality
Own data pipeline consistency
Ensure event schema conformance
Ensure event naming conformance
Ensure data type conformance
Ensure required field conformance
Ensure privacy compliance
Build transformation pipelines
Maintain transformation pipelines
Act as technical owner
Implement data quality checks
Monitor schema changes
Monitor validation failures
Monitor event completeness
Monitor event coverage
Monitor cardinality drift
Monitor volume anomalies
Monitor identity integrity
Monitor user stitching integrity
Enable trusted metrics
Ensure metrics are usable
Partner with analysts
Partner with data teams
Partner with product teams
Ensure metrics are clear
Ensure metrics are consistent
Ensure metrics are reusable
Ensure instrumentation meets needs
Support event payload design
Support schema design
Support instrumentation PR reviews
Support pre-release validation
Support experiment tagging
Support exposure tracking
How You'll Work.
Team & Collaboration
Work with software engineers; Collaborate with product analysts; Collaborate with data teams; Collaborate with product teams; Work with web engineers; Work with app engineers
Full Job Description
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 repo
Applying for this Digital Analytics Engineer role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on SmartRecruiters
- SmartRecruiters often includes a video screening step — check camera and mic permissions.
- Link your GitHub or portfolio directly in the profile section for technical roles.
- Applications may be reviewed by AI scoring before reaching a recruiter — use keywords from the job description.
ANONYMOUS · UNFILTERED
What do employees actually say about ASOS?
Real rants from real employees. Read before you apply.