Senior Data Analyst – Product Analytics & BigQuery
Salary: ₱135,000 – ₱150,000 per month
₱135,000–₱150,000 per month | Permanent WFH | Australian day shift
Turn customer, product and subscription data into decisions for a growing Australian nutrition and consumer technology company.
Compensation and Work Arrangement
Monthly rate: ₱135,000–₱150,000, based on experience
Location: 100% work from home in the Philippines
Schedule: Monday–Friday, 6:00 AM–3:00 PM Philippine time
Engagement: Long-term, full-time independent contractor
The Opportunity
Own analytics across mobile applications, subscriptions, e-commerce and digital marketing. You’ll work directly with the founder, leadership, product and marketing teams to understand customer behaviour, improve data reliability and identify opportunities for growth.
The analytics environment is already in place. Your role is to strengthen its foundations, establish consistent metrics and turn the data into clear business recommendations.
Known internally as Analytics & Insights Lead, this is a senior, hands-on individual contributor role. You’ll have the opportunity to shape how the business measures performance and makes decisions.
What You’ll Do
Own analytics from event tracking and metric definitions through to analysis, reporting and recommendations.
Analyse acquisition, activation, funnels, cohorts, retention and churn across the customer lifecycle.
Investigate subscription and revenue performance, including trials, conversions, renewals and cancellations.
Write advanced SQL in BigQuery, work with nested data and optimise queries.
Improve marketing and product instrumentation so customer behaviour is captured accurately.
Work with existing data pipelines and ETL tools, investigating missing, duplicated or conflicting data and reconciling sources.
Present clear insights and recommendations that help leadership, product and marketing decide what to do next.
What You’ll Need
End-to-end analytics ownership: Experience taking responsibility for analytics delivery and metric definitions, with clear examples of your personal contribution.
Product or customer-lifecycle analytics: Practical experience analysing funnels, cohorts, retention and churn.
Advanced SQL and BigQuery: Professional BigQuery experience, including nested data and query optimisation, supported by strong SQL skills.
Marketing and product event tracking: Experience defining, implementing or improving instrumentation.
Data quality and reconciliation: Experience investigating discrepancies and helping establish reliable, consistent data.
Pipelines and ETL: Experience working with data pipelines and ETL tools.
Subscription and revenue analytics: Experience analysing recurring-revenue performance and subscription behaviour.
Clear communication: Ability to explain findings and business recommendations to technical and non-technical stakeholders.
You should be comfortable taking initiative and working independently while collaborating with the teams responsible for the product and underlying systems.
Preferred Experience
Direct experience analysing Stripe data
Direct experience working with App Store Connect data
Creating dashboards and reporting for leadership
Relevant experience with other subscription platforms is welcome. Direct Stripe and App Store Connect experience is preferred, rather than mandatory.
Additional Experience We Value
Python for cleaning, backfills and analysis
A/B testing and statistical analysis
LLM integration, AI-output evaluation or conversation analysis
Structured data and predictive models for personalisation
These are additional strengths, not prerequisites for applying.
Why Join?
Take ownership of analytics and help shape how a growing business uses its data.
Work directly with the founder and senior decision-makers.
See your recommendations influence product, marketing and subscription performance.
Combine hands-on technical work with commercial problem-solving.
Build a long-term remote engagement on a consistent weekday schedule.
Your current title may be Senior Data Analyst, Product Analyst, Analytics Engineer or Analytics Lead. What matters is the work you have personally owned and the decisions your analysis has supported.
If you meet the essential requirements, we’d like to hear from you—even if you don’t have every preferred or additional skill.
If you have built trusted analytics foundations and know how to turn product and subscription data into better decisions, we’d like to hear from you.