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Data Engineering Manager (AWS) - ML & Analytics

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Summary

Head of Data at a high-growth European tech platform in Paris: own the end-to-end data strategy on an AWS Lakehouse, lead ML work (recommenders, predictive models, GenAI, A/B testing), and manage a small team of Analytics & ML engineers while turning data into business impact.

  • Paris
  • Permanent Contract
  • Fulltime



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We are partnering with a high-growth European tech platform operating at significant scale, building a product driven by real-time interactions and direct monetization.

With millions of users and a high volume of daily transactions, data sits at the core of both product innovation and business performance.


About the role :


As Head of Data, you will lead the data strategy end-to-end, acting as both a technical leader and business partner. You will own the full data scope from platform architecture to advanced Machine Learning use cases while managing a small, high-impact team.

You will work directly with executive leadership and product teams to turn large-scale data into actionable insights and intelligent features.


Responsibilities :


Data Platform & Architecture


  • Define and scale a modern AWS-based data platform (Lakehouse archi
  • tecture)Ensure data quality, reliability, and performance across pipelines
  • Own tracking strategy and event-based datamodeling


Machine Learning & Advanced Analytics


Lead development of:

  • Recommender systems
  • Predictive models (churn, monetization, engagement)
  • Advanced experimentationframeworks
  • Drive innovation using Deep Learning &GenAI


Business Impact & Analytics


  • Translate complex data into clear, actionable business insights
  • Influence product and growth decisions through data
  • Own key metrics: revenue, retention, LTV, acquisition performance


Leadership


  • Manage and mentor a small team of Analytics & ML
  • Engineers (≤4)Build strong data practices (SQL, DBT, code review, xuezdbg experimentation)
  • Foster a data-driven culture across the organization


Performance & FinOps


  • Monitor and optimize AWS data costs
  • Ensure scalability and efficiency of data pipelines


About you :


  • Experience leading Data / ML teams in high-scale environments
  • Strong hands-on expertise:Python, SQLAWS ecosystem (Redshift, S3, etc.)
  • Modern data stack (DBT, BI tools)
  • Proven experience with: Recommender systems or predictive modeling
  • Experimentation (A/B testing)Ability to connect technical topics with business impact

Skills

See also

Data Engineering jobs by country — openings, pay and top skills →

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