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# Senior Product Analytics Engineer

- **Company:** SoSafe
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Transformation, Data Security, Python (Programming Language), Mixpanel, Standard Sql, Usage Analysis, Large Language Models, Event Driven Architecture, Data Analytics, Amplitude Analytics, Heap (Data Structure)
- **Published:** September 23, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e36bfe7c52c770bb

## About the Role

* 5+ years of experience in an data analytics/ analytics engineering/ data science role, with significant experience directly supporting product teams in B2B companies.
 * Expert in the fundamentals of product analytics including building metric trees, experimentation, user activity & retention analytics, funnels & customer segmentation.
*
Excellent SQL skills, and strong experience using DBT for data transformations. Experience coding in Python is also relevant. Strong experience with data modelling for scale and reusability.

 * Demonstrated experience using current LLM offering to meaningfully improve your own or your team's workflows or results - with concrete examples of what you automated, sped up, or offloaded, and the measurable impact it had.
 * Ability to combine curiosity and ambition with a strategic mindset - continuously seeking better ways to deliver impact, scale insights, and drive business outcomes.
 * Experience working with event-based tracking data for web or mobile, and hands-on experience with a behavioral analytics tool e.g. Amplitude, Heap, MixPanel etc.
 * Ability to communicate findings succinctly and clearly to a wide variety of stakeholders so that they can draw conclusions quickly and make rapid decisions.
 * Relevant experience in cross-functional projects with GTM: proven valuable projects with Customer Success, RevOps or Product Marketing (e.g., churn early-warning, renewal/expansion predictors, win-loss usage mapping).

## Description

* Influence Decision-Making: Use a deep understanding of our product, users, and business to craft compelling data stories that guide product leaders in critical decisions.
 * Build reusable, scalable data products: collaborate with other engineers in developing data products that enable self-service analytics and democratize data access.
 * Build a governed self-service layer: define practices on event instrumentation & taxonomy for our event-driven architecture and self-service analytics tooling and enable Product and GTM peers on event instrumentation and insight generation.
 * Drive Data Literacy: Evangelize the use of data and empower teams to self-serve insights by increasing data literacy through enablement and close partnership.
 * Work AI-native: Continuously evaluate where LLMs and AI tooling can compress your workflow - from query generation to dashboard building to insight synthesis - and apply them deliberately to increase the speed and scope of what you and the team deliver.
 * Work cross-functionally with GTM: connect product usage to commercial outcomes (win/loss, expansion, renewal) and scale repeatable analyses/automations.


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