Analytics Engineer (Product Analytics)

ZYMIX is a Gen Z social super-app launching in the UK.

We are hiring a hands-on Analytics Engineer to join Growth Intelligence (GI) and bridge product analytics with data building—from event tracking and data modelling to dashboards and business insight.

What you'll do

• Design and maintain product event tracking plans, event properties and analytics data standards; work with Product and Engineering to ensure implementation supports future analysis.
• Build and maintain analytical data models and ADS tables across My SQL, Postgre SQL and Doris Event data; develop reusable SQL pipelines for product and business metrics.
• Own analytics data quality: reconcile production, Event and ADS data, validate tracking, investigate anomalies and establish reliable checks and metric definitions.
• Analyse acquisition, activation, engagement and retention; build funnel and cohort analyses, segment user behaviour and identify product and growth opportunities.
• Support A/B tests and product experiments by defining success metrics, evaluating results and translating findings into clear recommendations.
• Build and maintain Quick Sight datasets, dashboards and automated reports; monitor key metrics and improve reporting efficiency and self-service.
• Partner with Product, Engineering, Growth, Marketing and Operations to turn business questions into reusable data products and actionable insights.

What we're looking for

• 3+ years of relevant experience in product analytics, analytics engineering, growth analytics or BI, with evidence of independently owning data projects.
• Strong SQL skills and the ability to work confidently with joins, aggregations, window functions, reusable transformations and data troubleshooting.
• Experience with analytical data modelling, business metric definitions and building maintainable ADS or semantic-layer datasets.
• Practical understanding of event tracking design, event properties and how tracking decisions affect funnels, retention and product analysis.
• Experience building BI dashboards and automated reporting; able to turn raw data into clear business conclusions and recommendations.
• Strong logical thinking, ownership and communication skills; able to work effectively with both technical and business teams in English.
• Nice to have
• Quick Sight, Tableau or Power BI; Amplitude, Mixpanel or GA4; Airbridge or Adjust; mobile-app, social-product, growth or experiment-analysis experience.
• Understanding of data warehouse architecture and ETL processes; exposure to Airflow, dbt, Git or Python is helpful but not required.
• How the role works

This is not a read-only analyst role.

You will own the GI-controlled analytics schema, transformations and BI datasets, with appropriate development access.

Engineering remains responsible for application databases, event collection and core platform availability; you will partner with them on source and infrastructure changes.

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