Senior Marketing Analyst

Role Overview

We are seeking a Senior Marketing Analyst who possesses a rare blend of technical literacy and high-level business acumen. While our Data Engineering team handles the core infrastructure and pipeline builds, you will be the "Architect of Insight."

You aren't just looking at marketing KPIs; you are connecting marketing touchpoints to bottom-line business metrics like LTV , Retention , and Cohort-based CAC .

Key Responsibilities

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  Strategic Requirements Mapping: Act as the lead translator between Marketing and Data Engineering. You will define the logic for unified data models and oversee their implementation to ensure they meet business needs.
  


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  Advanced Data Auditing: Use your knowledge of APIs and SQL to audit data flows. When a dashboard looks "off," you should be able to identify if the issue lies in the API source, the transformation script, or the business logic.
  


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  Full-Funnel Analytics: Build and own end-to-end dashboards that connect top-of-funnel advertising data with back-end customer behavior data.
  


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  Unit Economics Mastery: Lead the analysis of Customer Acquisition Cost (CAC) and Lifetime Value (LTV) . You will provide the "Why" behind the "What," helping the team shift budget to the most profitable channels.
  


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  Stakeholder Management: Present findings to leadership and work closely with Data Engineers to prioritize technical fixes that unblock marketing insights.
  

Technical Requirements

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  The "Engineering-Adjacent" Mindset: You must be deeply familiar with how data travels from an API call into a Google Cloud environment. You don't need to build the pipeline, but you must be able to troubleshoot it.
  


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  GCP & SQL Proficiency: Advanced-level SQL is a must. You should be comfortable navigating BigQuery to validate data and build custom views.
  


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  Visualization Expert: Advanced experience with Looker , Metabase , or similar, creating scannable, executive-level dashboards that tell a story.
  


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  Marketing Tech Stack: Deep understanding of the backend of Meta Ads, Google Ads, and GA4 (specifically how they pass parameters like UTMs and GCLIDs).
  


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  Business Analytics: Proven track record of connecting marketing spend to actual revenue and customer retention metrics.
  


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   Programming & Scripting: Proficiency in data analysis tools and programming languages (e.g., SQL, Python, R).
  

Professional & Soft Skills

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  The "Business Eye": You don't just move data; you understand why it matters. You have a deep interest in performance marketing and unit economics.
  


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  Communication: Exceptional ability to explain technical roadblocks to marketers and marketing goals to engineers.
  


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  Proactive Problem Solving: You identify gaps in the data journey before they become reporting issues.
  

Marketing Analytics Experience: you should be familiar with metrics and data like ad spend, clicks, installs, reach, impressions and ad engagement metrics