Analytics Engineer

The Customer Relationship Data Team is dedicated to delivering actionable insights to a broad range of stakeholders—including Strategic Leads, Digital Product Managers, Country Operations, and Unified Marketing teams—to drive data-informed decision-making.

We design and deploy innovative technical solutions for our internal users, prioritizing operational excellence and daily user satisfaction. In the context of a new external consultancy opening, we are seeking an Analytics Engineer to join our team in Paris.

360 data processing and readiness for MMM purposes

• Help the Retail Marketing team and their external MMM (Marketing Mix Modeling) vendor access data regarding levers that have an impact on global sales.
• Meet with the data owners, understand their data stored in the datalake and manipulate it according to their standards.
• Process the data and make it accessible so the MMM vendor can use it for their MMM algorithm.
• Receive the MMM vendor’s data model (input and output of their MMM algorithm) and store it in the insight layer of our datalake.

Customer Relationship Insight excellency

• Enable intelligent analytics by building robust, reliable and relevant datasets.
• Build and model the semantic layer of the business domain (CRM & Customer Relationship) in collaboration with the BI Engineer, PM Data and the governance manager.
• Automate and industrialize the data transformation pipelines used for dashboards, AI models and data analysis.
• Contribute to the development of our technical stack strategy with tech leads.
• Apply best practices, guarantee the quality of exposed data and the performance of flows.
• Maintain and rethink existing datasets and pipelines to serve a wider variety of use cases.
• Contribute actively to our community of analytics engineers and data engineers.

Technical environment

• Data-platform: Amazon Web Services, Databricks, S3
• Code Programming: SQL, Python, Scala
• Data orchestration: Airflow
• Data modeling: dbt
• Software versioning & Delivery: Git, Github, Make

What you'll need to succeed

• You have at least 5 years' experience as an Analytics Engineer or Data Engineer.
• You have significant experience on one of the main AWS / GCP / Azure clouds, and know how to use components (e.g. Databricks) and schedulers (Airflow, etc.) and optimize their performance.
• You are fluent in the following languages: SQL and/or Python.
• You've mastered the implementation of data transformation pipelines with dbt and you have a strong understanding of optimization possibilities, which is essential given the high volume of data involved.
• You have experience with an orchestrator (Airflow, Luigi, Prefect, Dagster…) in order to implement the reporting pipelines within the team.
• You have experience in dimensional modeling (Kimball, Data Vault, OBT).
• Your peers recognize you for your strong technical aptitude.
• You're comfortable with development tools: Git, Github, CI/CD, VSCode/Pycharm, Terminal.
• You have foundations in CI/CD (Github Actions) with core concepts (testing, publishing and deploying artifacts) applied to the AE context.
• You understand the data lifecycle and are comfortable with the concepts of data lineage, data governance and documentation.
• It would be expected that you conduct gap analysis (table migrations, data models comparison) with rigor and accuracy.
• You have a good level of English, enabling you to communicate both orally and in writing with our customers and partners (across 60 countries). This will be key for the international MMM project.
• You enjoy working in an agile, collaborative environment (Scrum, etc.).
• You have a strong sense of service.
• You are particularly sensitive to the impact of physical activity and wellness on your leadership style and team life!