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Product Analytics Implementation Specialist

12 months

In short

Join Leonardo.Ai as a Product Analytics Implementation Specialist to validate, document, and improve behavioural data tracking across GA4, Heap, Braze, and other tools. Help teams make data-informed decisions with clear, consistent event data and dashboards.

Where
Remote · New Zealand
Leonardo.Ai
Leonardo.Ai
  • AI & VR

Builds an AI platform that generates images and creative assets for millions of users.

0 open roles

Responsibilities

  • Support tracking quality: Validate event data across GA4, Heap, and Braze, and help teams resolve data gaps or inconsistencies.
  • Collaborate with engineers: Partner closely to QA GTM implementations, SDK calls, and data-layer logic.
  • Document and improve: Develop naming conventions, metadata standards, and reference guides that facilitate scalable and straightforward tracking.
  • Investigate and problem-solve: Utilise GTM Preview, Heap Inspector, and browser developer tools to identify and resolve event issues.
  • Empower decisions: Provide reliable, well-documented data that helps every team learn from user behaviour and product impact.

Skills

  • Digital Analytics Expertise: Experience in digital or product analytics, including hands-on GA4 + GTM implementation and troubleshooting.
  • Comfort with Leonardo’s Stack: Familiarity with Heap, Braze, or LaunchDarkly or curiosity and eagerness to learn them quickly.
  • Technical Understanding: Good grasp of data-layer design, tag debugging, and validation workflows that keep events accurate.
  • Care and Craft in Your Work: Pride in organised, detailed work that supports others and keeps systems running smoothly.
  • Collaborative Communicator: Enjoy connecting technical and non-technical teammates and making data logic easy to understand.
  • Love Documentation: Experience writing or maintaining tracking specs, QA checklists, or governance documentation that others rely on.
  • Broader Tagging Experience: Familiarity with server-side tagging or event forwarding (e.g. GTM Server, Segment).
  • Cross-Tool Quality Assurance: Experience running QA and reconciliation between GA4, Heap, or Braze to ensure data consistency.
  • Experimentation Mindset: Exposure to feature flags or experimentation tools, such as LaunchDarkly, and an understanding of how they shape user experiences.
  • Curiosity About Creators: An interest in how people use Leonardo’s platform, and how behavioural data helps us tell their creative stories.
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