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Singapore
Onsite
1. MarTech Architecture, Tracking, Auditing & Proactive Enrichment
Web Tracking, Debugging & Ad Signal Routing: Own the end-to-end web tracking architecture across Google Analytics (GA4) and Google Tag Manager (GTM). Define and document Data Layer requirements for the engineering team to implement, and ensure accurate web tracking signals and conversion events are seamlessly routed back to key ad platforms via GTM.
App Tracking & MMP Integration: Partner closely with the engineering team to implement, test, and maintain tracking across mobile apps (AppsFlyer, Firebase) for SDK events and Server-to-Server (S2S) events. Architect a standardized event taxonomy, oversee SDK integrations, and manage overall AppsFlyer health.
Ad Platform Tracking Optimization: Take deep ownership of exactly how ad platforms consume our data. Partner closely with internal User Acquisition (UA) channel owners to unblock tracking bottlenecks, troubleshoot platform-specific signal loss, and proactively enrich tracking signals (e.g., passing backend LTV scores or customized events back to ad platforms). Act as the technical authority who translates complex media platform requirements into actionable tracking solutions to maximize campaign performance.
Comprehensive Stack Auditing & Enrichment: Lead end-to-end audits of the tracking and reporting foundation to resolve data gaps, latency issues, and discrepancies across tracking tools, internal BI, and ad platforms. Move beyond routine maintenance by establishing automated QA monitoring to instantly detect event drop-offs or tracking anomalies, while strictly managing privacy-centric tracking and consent routing.
2. Advanced Measurement, Attribution & Incrementality Analysis
Attribution Strategy & MMM: Support the build of measurement solutions across the full attribution spectrum—from foundational models (Last-Touch) to advanced frameworks (Multi-Touch Attribution [MTA] and Media Mix Modeling [MMM]). Partner with Data Science and Engineering to ensure clean, structured signal data is feeding into these models. Help operationalize these measurement models and triangulate insights across these frameworks and growth metrics to evaluate true user acquisition performance.
LTV & Cohort Analytics: Analyze user acquisition performance, customer acquisition cost (CAC), lifetime value (LTV), and user cohorts. Translate these complex data sets into actionable insights to scale high-performing channels and inform broader growth strategies.
Incrementality Testing & Analysis: Support the design, implementation, and analysis of incrementality tests to measure the true causal impact of growth efforts and validate overall ROI.
3. Data Engineering Collaboration & Advanced BI
Data Pipeline Collaboration: Partner with Data Engineering to manage growth data requests, ensuring event streams are clean, structured, and accurately mapped into growth data pipelines.
Advanced SQL & Data Modeling: Write complex SQL to mine large datasets, build custom tables, and execute high-velocity ad-hoc analysis.
Dashboarding & AI Automation: Build and maintain automated dashboards using Tableau and Databricks. Integrate AI Agents to streamline reporting workflows and surface deeper, more actionable insights for leadership and business teams.
4. Cross-Functional Project Management
Technical Translation: Collaborate with Growth, Product, Engineering, and Data teams to translate complex marketing and analytics use cases into precise technical requirements and actionable project tickets.
Internal Documentation: Create, scale, and maintain comprehensive internal documentation covering our tracking architecture, event taxonomies, and growth data schemas.
Bachelor’s degree (or higher) in Data Analytics, Computer Science, Information Systems, Business, Statistics, Marketing, or a related quantitative field.
4+ years of dedicated experience in MarTech tracking, growth analytics, and digital marketing data analysis. Experience in Crypto, FinTech, or Technology is a strong plus.
Deep, hands-on proficiency with Google Analytics 4 (GA4) and Google Tag Manager (GTM), with the ability to define Data Layer requirements, route ad tracking signals, and debug network setups.
Deep expertise in ad platform signals and mechanics. You must know exactly how ad platforms consume data and have hands-on experience solving platform-specific tracking challenges, including Meta CAPI, AEM, Google conversion signals, event postbacks to DSPs and ad networks.
Deep expertise in mobile app tracking, specifically with AppsFlyer and Firebase, including experience standardizing event taxonomies and overseeing both SDK and Server-to-Server (S2S) event integrations.
Understanding of advanced attribution frameworks (MMM, MTA) and proven experience designing and executing incrementality tests (holdouts, conversion lift studies).
Understanding of digital marketing economics, including user acquisition optimization, customer acquisition cost (CAC), lifetime value (LTV), cohort analysis, and paid media strategies.
Understanding of CDP/CRM tools (e.g., Segment, Braze) and how they route data signals to downstream channels and systems.
Understanding of privacy-centric tracking mechanisms (e.g., Google Consent Mode, SKAdNetwork).
Advanced SQL skills for mining large datasets, creating custom tables, and executing ad-hoc analysis, alongside mandatory hands-on experience with Databricks and Tableau.
Exceptional communication skills with a proven ability to translate complex marketing and business needs into precise technical tickets for Engineering and Data teams.
Strong organizational skills with experience building comprehensive internal technical documentation and managing multiple high-priority projects in a fast-paced environment.