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
