Globe · 15f The Globe TowerPrepare for this interview
EliteAI-generated questions, company research, and talking points tailored to this role
At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal. Job Description This role owns the behavioral measurement foundation that makes journey analytics reliable and reusable. Stabilizes instrumentation across digital channels, runs QA and governance, and enables true end-to-end journey measurement by defining the journey blueprint, linking keys, and data contracts in partnership with Data and system owners. Focus Areas 1. Instrumentation governance & QA (primary): tracking plan, event taxonomy, specs, release verification, and ongoing health checks across GA4/Firebase, FullStory, and shared behavioral signals used by Braze/Appsflyer where relevant. 2. Decision-grade measurement foundations: metric/measurement dictionary, funnel definitions, and interpretation guidance for priority journeys/episodes. 3. End-to-end journey measurement enablement (digital + backend): define journey stage models, source-of-truth mapping, timestamps, IDs, and data contracts needed to stitch digital + operational signals. 4. Data quality operations: monitoring for missing events/parameters, spikes/drops, schema drift, duplication/noise reduction. DUTIES AND RESPONSIBILITIES: 1) Instrumentation Clean-up & Standardization Audit current tracking (GA4/Firebase, FullStory, AppsFlyer/shared event signals) and maintain an instrumentation health scorecard . Create and maintain the tracking plan + event taxonomy (naming, required parameters, definitions). Reduce noise by de-duplicating/merging low-value or inconsistent events; define "must-have" attributes for priority funnels. Ensure FullStory configuration supports diagnostics (capture strategy, masking, events/segments, funnels/workflows). 2) Governance, QA, and Data Quality Operations Run the operating model: intake → spec → build support → QA → release verification → ongoing health checks . Partner with Engineering on test plans, post-release verification, and regression checks. Implement ongoing event health monitoring (missing events/params, spikes/drops, schema drift, duplication). 3) Product Measurement Foundations (Decision-Grade Analytics) Co-design success measures, funnels, and behavioral signals for priority journeys (e.g., onboarding, reload/purchase, support, retention, multi-product). Maintain a measurement dictionary : metric definitions, calculation logic, and "do/don't interpret" guidance. Enable diagnostic loops (FullStory + funnel analytics): friction identification, impact quantification, and fix validation. 4) End-to-End Journey Measurement Enablement (Digital + Backend Signals) Identify backend source-of-truth systems per priority episode (orders, billing/payments, provisioning, care tickets, network/service events, etc.). Define the end-to-end event map: app vs backend events, key timestamps, IDs, and stage progression. Partner with Data org to define linking keys + data contracts and document canonical journey datasets for reuse 5) Cross-Team Alignment & Enablement Align shared behavioral signals with MarTech Analytics and activation teams to support lifecycle/personalization use cases-without owning campaign/CRM reporting. Train squads on measurement best practices and instrumentation discipline; escalate risks/trade-offs clearly. Top Deliverables Instrumentation Health Scorecard - a recurring audit of tracking completeness, required parameter coverage, duplication/noise, and known gaps for priority journeys. Tracking Plan + Event Taxonomy - standardized event naming, required fields, definitions, and change control for all critical funnels. Operating Model for Instrumentation - intake/spec templates, versioning, QA checklists, and release verification workflow. Episode KPI Dictionary / Measurement Dictionary -A single source of truth documenting how metrics are calculated and interpreted. Definition + formula, Grain, Filters/exclusions, Data sources, Known caveats, Owner + last updated End-to-End Journey Measurement Blueprint - documented backend sources, event map, linking keys, and data contract requirements handed to the Data org for execution. Event Health Monitoring + Weekly Health Review - includes ongoing freshness, duplication, and schema drift checks. KPIs Tracking completeness and accuracy for priority journeys (coverage + required parameters) Reduction in duplicate/noisy events and inconsistent naming Faster QA and release verification cycle time Improved diagnostic cycle time (issue → insight → fix) supported by FullStory workflows % of priority journeys with end-to-end measurement coverage (digital + backend) Adoption of shared definitions across Product and MarTech Analytics
How well this role fits your profile.
Worked at globe? Share your experience