Role Overview

You will play a critical role in the structuring, development, and delivery of large-scale technology solutions for Publicis Media France. You will lead engineering teams across data engineering, backend development and DevOps, owning the technical roadmap of the Data Platform and ensuring its scalability, reliability and long-term evolution.

Key Responsibilities / Missions

Technical Leadership & Architecture

Lead the design and evolution of scalable platform architectures. Define and enforce architecture, development and security standards. Make strategic technical decisions aligned with business and product needs, and promote engineering best practices across teams.

Data Platform Delivery (SILVER / GOLD)

Drive the development of curated Data Platform layers (SILVER and GOLD datasets). Ensure datasets are reliable, standardized and analytics-ready, enabling downstream reporting, activation and advanced use cases.

Data Governance

Contribute to the definition and implementation of Data Governance practices, including documentation, ownership, access control, lineage and governance standards, as part of the platform roadmap.

Data Quality

Embed Data Quality as a core platform capability by defining quality standards, implementing automated tests, monitoring, and ensuring strong documentation and traceability across pipelines.

AI Enablement & Exploratory Topics

Lead AI enablement initiatives as part of the platform roadmap, including exploratory work around Cloud and Platform AI Agents. Identify opportunities where AI can improve data quality, governance, observability, automation and developer productivity, while ensuring responsible and secure adoption.

DevOps & Platform Engineering

Promote Infrastructure-as-Code, CI/CD pipelines, testing strategies and deployment automation. Establish coding guidelines, documentation standards and review processes to ensure engineering excellence.

Team Leadership & Skill Development

Lead and mentor offshore engineering teams. Define skill development plans across data engineering, cloud platform engineering, governance, quality and AI topics. Encourage knowledge sharing and allocate capacity for proof-of-concepts and innovation.

Core Technology Stack

Google Cloud Platform (BigQuery, Cloud Storage, Cloud Functions, Cloud Run, Pub/Sub), Airflow / Cloud Composer, DBT, Python, SQL, Terraform, CI/CD pipelines.