Digital Analytics Engineer

ASOS; Greater London; On-site; GBP 70,000 - 95,000; Full time

Benefits offered by this job

Employee discount

Employee sample sales

Paid annual leave

Private medical care

Annual appreciation payment

Learning opportunities

Job summary

ASOS seeks a Digital Analytics Engineer to shape how we understand customer behaviour across our digital estate. You will own data modelling, instrumentation, and end‑to‑end data quality to enable high‑quality experiments and trusted insights.

You will partner with product, analytics, and engineering teams to design scalable behavioural models, robust event contracts, and reliable data pipelines that power self‑serve analytics and executive reporting.

Qualifications

• 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.

Responsibilities

• 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
• 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
• In collaboration with 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
• 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
• 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

Skills

SQL

Databricks

Spark

DBT

Python

Product analytics

Data pipelines

Data quality

Collaboration

Tools

Databricks

Spark

DBT

Python

Job description

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

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

Qualifications

We’re Looking For

• 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

Summary

Type: Full-timeFunction: Information TechnologyExperience level: Mid-Senior LevelIndustry: Retail