1-2 years experience in digital analytics, instrumentation QA, or data quality operations
Experience validating event tracking across web or mobile products
Experience working with cross-functional product and engineering teams
Technical Skills
Familiarity with GA4 or Firebase analytics
Familiarity with FullStory or behavioral session analytics tools preferred
Basic to intermediate SQL for data validation and investigation
Comfortable working with spreadsheets and data validation tools
Knowledge
Understanding of event-based analytics models
Familiarity with instrumentation concepts such as event parameters, funnels, and user flows
Understanding of analytics data reliability and quality risks
Competencies
Strong attention to detail and data accuracy
Structured and disciplined operational approach
Ability to detect patterns and anomalies in behavioral data
Strong doc
Benefits
Health insurance
Additional Information
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 ensures that behavioral data collected across digital products is reliable, complete, and decision-grade. The Product Analytics Analyst - QA & Data Quality is responsible for validating instrumentation quality, monitoring event health, detecting tracking defects, and maintaining operational discipline in how analytics data is verified and maintained. Working closely with Product Managers, Engineering teams, and the Instrumentation / Measurement lead, this role ensures that analytics signals across platforms such as GA4/Firebase, FullStory, and shared event streams remain consistent and trustworthy.
This role enables faster and more confident decision-making by owning the operational reliability of behavioral measurement across releases and production environments.
DUTIES AND RESPONSIBILITIES:
1. Instrumentation QA & Release Validation
Validate instrumentation for priority product releases and journey improvements.
Ensure events fire correctly across GA4/Firebase, FullStory, and related analytics platforms.
Confirm required parameters, values, and event sequencing match approved specifications.
Support pre-release validation and post-release verification of instrumentation.
2. Event Health Monitoring & Data Quality Operations
Monitor behavioral signals for missing events, parameter gaps, spikes, drops, duplication, and schema drift.
Investigate anomalies and identify root causes with Engineering and Analytics teams.
Maintain recurring data quality checks and monitoring routines.
Identify recurring tracking issues and support improvements to instrumentation standards.
3. Instrumentation Health Reporting
Maintain and update the Instrumentation Health Scorecard for priority journeys.
Provide regular summaries of measurement quality risks and unresolved tracking issues.
Track defects from identification to resolution with appropriate owners.
Highlight systemic issues affecting measurement reliability.
4. Instrumentation Operating Model Support
Support the instrumentation operating rhythm from specification to release verification.
Execute standardized QA checklists and validation routines.
Maintain issue trackers and documentation for tracking defects and quality gaps.
Contribute improvements to QA practices and measurement governance processes.
5. Cross-Team Enablement
Support squads in understanding instrumentation QA expectations and validation steps.
Help improve measurement discipline across Product and Engineering teams.
Share recurring issues and best practices to reduce future tracking defects.
Top Deliverables
Instrumentation QA Verification Pack: Structured validation checklists and documentation confirming instrumentation is working correctly during releases.
Instrumentation Health Scorecard: A recurring view of tracking completeness, parameter coverage, duplication, schema consistency, and known gaps across priority journeys.
Event Health Monitoring Log: A structured log of tracking defects including missing events, parameter issues, spikes/drops, duplication, and schema drift.
Weekly Data Quality Review: A summary of instrumentation issues, new defects, resolution progress, and risks affecting measurement reliability.
Defect Triage Tracker: A documented list of instrumentation issues with root cause analysis, assigned owners, and resolution status.
Success Measures
Success in this role will be measured through improvements in measurement reliability and faster detection of instrumentation issues.
Key indicators include:
Higher tracking completeness across priority journeys
Reduction in duplicate or inconsistent events
Faster instrumentation QA turnaround time for product releases
Reduction in unresolved tracking defects
Increased confidence in behavioral analytics used by Product teams
Improved stability of analytics signals across releases
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