Digital Analytics Engineer: Data Pipelines & Experiments

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

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.