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# Analytics Engineer - Tag Manager

- **Company:** Royal Mail
- **Location:** London, UK
- **Salary:** £53,661.0
- **Contract:** Permanent contract
- **Skills:** HTML, JavaScript (Programming Language), Artificial Intelligence, Data Analysis, Cascading Style Sheets (CSS), Information Engineering, Data Integration, Data Systems, Tag Management, Web Analytics, Google Tag Manager, ReactJS, Data Layers, Adobe, Tealium, React Native, Software Coding
- **Published:** September 8, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5874912483

## About the Role

* Strong experience in Analytics Engineering, Data Engineering or Digital Analytics.
 * Hands-on expertise with Tealium IQ,Google Tag Manager (GTM), Adobe Launch or similar tag management platforms.
 * Strong understanding of digital analytics implementations, tagging and data layer design.
 * Technical coding skills in:

 * JavaScript
 * HTML
 * CSS

Exposure to React and/or React Native environments.Experience integrating data from multiple sources and working within modern analytics ecosystems.Ability to translate business requirements into technical specifications and explain technical concepts to non-technical stakeholders.Strong attention to detail with a focus on building scalable, reliable solutions.

This is an excellent opportunity for a technically strong analytics professional who enjoys combining coding, data engineering and business understanding to drive better digital insights

## Description

This is a highly technical, hands-on role working closely with Product, Analytics and Engineering teams to ensure high-quality, reliable data is available for analysis, optimisation and decision-making., * Own the implementation and optimisation of Tag Management solutions across web and app platforms.

 * Develop and govern data layer specifications, SDRs and tracking documentation.
 * Integrate and model data from multiple sources to create robust analytics datasets.
 * Support customer journey analysis, experimentation and conversion optimisation initiatives.
 * Ensure analytics data quality through testing, validation and monitoring.
 * Leverage AI-enabled tools and techniques to improve analytics engineering processes.
 * Partner with technical and business stakeholders, translating requirements into effective data solutions.