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Company 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.
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
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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
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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
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