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

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

Digital Analytics Engineer