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Ledger Logo Ledger · IT - Software Development

Senior Analytics Engineer

France, Paris · Job Posted February 16, 2026
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Job Description

The Data team is responsible for leveraging data to drive strategic business decisions and enhance our product offerings. As a core member, you will be responsible for end-to-end data projects—from defining metrics and building robust data pipelines to deploying analytical models. Your insights will be essential for monitoring company performance, understanding user behavior across various protocols, and contributing directly to Ledger's growth and security strategies.

Job Responsibility

  • Design, build, and maintain robust, scalable data pipelines (ELT) using dbt and Airflow, ensuring our Snowflake warehouse is optimized for both performance and clarity
  • Bridge the gap between raw, unstructured technical data (including on-chain events) and clean, actionable business entities
  • Act as a technical partner to Product, Engineering, and Finance teams, translating high-level business questions into technical requirements and analytical frameworks
  • Implement version control, CI/CD for data, and automated testing to ensure the highest levels of data quality and reliability
  • Perform deep-dive analyses to track revenue, identify user segments, and optimize product features.

Requirements

  • 4+ years (Senior level) of professional experience in Analytics Engineering, Data Engineering, or a Data Science role
  • Exceptional proficiency in SQL
  • Comfortable with complex window functions, performance tuning, and modeling in Snowflake
  • Deep experience with dbt (data modeling, macros, testing) and workflow orchestrators like Airflow
  • Strong programming skills in Python for data manipulation, automation, and building data-intensive applications
  • Engineering Mindset: You treat data code like software—version control (Git), documentation, and modularity are second nature to you.

Nice to have

  • Curiosity for Web3
  • Experience with time-series analysis, anomaly detection, or predictive modeling
  • Any previous experience with on-chain data (e.g., Dune Analytics, Flipside, or indexing protocols) is a major advantage.

What we offer

  • Flexible work options - Our hybrid policy allows employees to work from home up to 3 times per week
  • Health & Wellness support - Health and Life Insurance
  • Financial growth opportunities - Employees can become shareholders in Ledger as well as other financial benefits depending on your country of work
  • Commuter allowance - Ledger offers a commuter allowance to contribute to your preferred means of transportation
  • Learning & Development - A comprehensive suite of training solutions providing a personalised learning experience for every employee.
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