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Open nowPosted 6 hours ago

Senior Marketing Data Analyst

AF26 open roles

Where
France, Remote
Work mode
Remote
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Your applicationOpen nowSenior Marketing Data AnalystAF · France, Remote

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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. AF postings stay open a median of 1 days.

Share of postings closed within
  1. 1.9%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.1%30 days
This job: posted 6 hours ago

AF median: 1 days open

The posting

About the Role

We are looking for a Senior Marketing Data Analyst to own our marketing data pipeline end-to-end, from extraction, through transformation in BigQuery, to data analysis and client-ready dashboards in Tableau.

This is a high-trust, high-autonomy role. You'll be the last line of defense before data reaches clients and internal stakeholders, so precision, proactive communication, and independent problem-solving matter just as much as technical skill.

What You'll Own

Data Pipeline & Extraction

  • Manage data extraction from ad networks, MMPs (Adjust, AppsFlyer), and analytics tools (GA4) via Improvado into Google BigQuery.
  • Monitor pipeline health proactively, catch and flag broken feeds, delayed loads, or schema changes before they affect downstream reporting, not after a client notices.

Data Transformation & Modeling

  • Build and maintain SQL transformations and data models in BigQuery, establishing clean, correct relationships across multiple data sources.
  • Write documented, reusable queries and scripts (SQL, Python and/or R) rather than one-off fixes.

Data Analysis & Insights

  • Calculate and model LTV by cohort, channel, and campaign; own churn calculation and reporting.
  • Build predictive models for churn and LTV to support proactive retention and budget decisions.
  • Run cohort and retention curve analysis to track user quality over time.
  • Analyze CAC and monitor CAC:LTV ratios to guide acquisition spend; measure ROAS/ROI by channel and campaign.
  • Conduct funnel and conversion drop-off analysis to identify where users are lost.
  • Support attribution modeling (multi-touch/incrementality) to clarify true channel contribution.
  • Produce revenue, spend, and user-growth forecasts; contribute to media mix and budget allocation modeling.

Dashboarding & Visualization

  • Design and maintain interactive Tableau dashboards that blend multiple data sources with correct joins and relationships.
  • QA every dashboard and report for accuracy before it reaches a client or stakeholder, numbers tie out, filters work, nothing is stale.

Quality & Ownership

  • Take full ownership of data accuracy from source to dashboard; you self-check rather than relying on someone else to catch mistakes.
  • Proactively flag anomalies, discrepancies, or risks to your manager and stakeholders as soon as you spot them, no surprises, no last-minute fire drills.

Collaboration & Communication

  • Partner directly with UA/performance marketers, clients, and stakeholders to define KPIs and refine reporting frameworks.
  • Communicate clearly and promptly: status updates, blockers, and caveats are shared before they become problems, not after.

What success looks like in your first 90 days:

  • Full fluency with our Improvado → BigQuery → Tableau pipeline and current dashboard suite.
  • Zero client-facing data-quality escalations traceable to preventable errors.
  • At least one process improvement, automation, or QA safeguard you identified and implemented on your own initiative.

What We're Looking For

  • 5–8 years of experience in data analytics, ideally within marketing, digital advertising, or performance-driven environments.
  • Strong SQL (BigQuery) and working proficiency in Python or R.
  • Hands-on experience with Improvado or a comparable UI-based data extraction tool.
  • Advanced Tableau skills, you can build multi-source dashboards with correct data relationships, not just single-table charts.
  • Experience with Adjust, AppsFlyer, GA4, and major ad networks.
  • Solid grasp of core marketing analytics metrics, LTV, CAC, churn, ROAS, retention/cohort analysis, and how to turn them into recommendations.
  • Comfortable building basic predictive/statistical models (e.g., churn or LTV prediction) using SQL, Python, or R.
  • A demonstrated track record of catching your own mistakes before they ship (be ready to talk through a real example in the interview).
  • Comfortable working with minimal supervision: you flag problems and propose solutions rather than waiting to be asked.
  • Excellent written and verbal English; you can explain data issues clearly to non-technical stakeholders.

Bonus Points

  • Experience designing and analyzing A/B tests.
  • Familiarity with GCP tooling beyond BigQuery (Cloud Functions, Composer/Airflow, dbt).
  • Deeper machine learning experience for predictive analytics (beyond core churn/LTV models).
  • Additional languages beyond English.
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