Data Engineering Manager - Paris

Vestiaire Collective; Paris; Hybride; EUR 80 000 - 100 000; Plein temps

Avantages offerts par ce poste

Competitive compensation

Flexible working model

Dedicated learning budget

Health coverage

Résumé du poste

A leading fashion sustainability firm in Paris is seeking an Engineering Manager to lead a Data Platform team. You will manage a small team of Senior Data Engineers, focusing on the reliability and scalability of the core data infrastructure. Expect to work closely with Analytics Engineers and Data Scientists to enhance usability and drive initiatives focused on AI and ML. This role offers a hybrid working model, competitive compensation, and the opportunity to make a significant impact in the fashion industry.

Qualifications

• Strong experience with Python and SQL.
• Solid experience with data processing tools like Spark and Kafka.
• Experience with workflow orchestration tools like Airflow.

Responsabilités

• Lead and grow a team of Data Engineers.
• Drive reliability and scalability of data infrastructure.
• Participate in design discussions to support problem-solving.

Connaissances

Python

SQL

Distributed data processing (Spark, Kafka)

Workflow orchestration (Airflow)

AWS

Docker

Kubernetes

Outils

Snowflake

MLflow

SageMaker

Description du poste

About The Role

You will join the Data Platform team at Vestiaire Collective as an Engineering Manager, leading a team of 2 to 3 Senior Data Engineers. We are a lean, collaborative team responsible for the ingestion, transformation, and ML infrastructure that powers the entire organization.

What You’ll Do

• Lead & Grow the Team
• Manage and support a team of 2 to 3 senior Data Engineers, providing regular feedback, coaching, and career development.
• Foster a collaborative, high-performing, and accountable team environment.
• Ensure strong ownership, clarity of priorities, and high engineering standards.
• Own Data Platform Reliability & Foundations
• Drive the reliability, scalability, and evolution of our core data infrastructure (Spark, Kafka, transformation layers).
• Define and enforce best practices around data quality, observability, and monitoring.
• Ensure the platform remains trusted, stable, and scalable as usage grows.
• Drive Platform Enablement & Efficiency
• Lead initiatives to improve performance and optimize costs (FinOps mindset).
• Own the evolution of orchestration tools (Airflow) and ensure a smooth developer experience for data consumers.
• Partner with Analytics Engineers and Data Scientists to continuously improve the platform’s usability.
• Enable AI & Future Innovation
• Define and support the infrastructure strategy for AI and ML use cases.
• Enable scalable solutions for ML workflows, model deployment, and LLM integration.
• Anticipate future needs and ensure the platform is ready for AI-driven products and operations.
• Contribute to Technical Direction
• Guide architectural decisions and ensure pragmatic, maintainable solutions.
• Stay close to the tech: participate in design discussions and support complex problem-solving.
• Act as a bridge between engineering, data, and product stakeholders.
• People Leader: You enjoy growing engineers and building strong, autonomous teams.
• Technical Anchor: You have a strong data engineering background and can guide technical decisions.
• Pragmatic: You focus on impact, scalability, and maintainability over complexity.
• Collaborative: You work effectively across teams and value shared ownership.
• Product & User-Oriented: You care about the experience of internal users (Data Scientists, Analysts, Engineers).
• Forward-Thinking: You are curious about the evolution of data platforms, AI, and modern data ecosystems.

Who You Are

• Strong fundamentals and leadership matter most.

Your Skills

Core Engineering & Data

• Strong experience with Python and SQL
• Solid experience with distributed data processing (Spark, Kafka)

Platform & Infrastructure

• Experience with workflow orchestration (Airflow)
• Familiarity with AWS, Docker, Kubernetes
• Experience working with modern data stacks (e.g., Snowflake, dbt)

Leadership

• Previous experience managing or mentoring engineers
• Ability to drive technical decisions and prioritize effectively

MLOps & AI (plus)

• Experience with ML pipelines and tools (MLflow, SageMaker)
• Exposure to LLM/GenAI infrastructure (e.g., Vector DBs, Bedrock)

Nice-to-Haves

• Experience building internal data platforms
• Familiarity with Infrastructure as Code (Terraform)
• Exposure to FinOps and cost optimization practices

Tech Stack

Python, Spark, Kafka, Airflow, Kubernetes, Snowflake, and modern ML platform tools (e.g., MLflow, SageMaker)

What We Offer

• Purpose-driven work at scale Join a company reshaping the fashion industry towards circularity, you directly contributes to reducing waste and extending the life of luxury items
• High-impact scope & ownership Work on products used globally, where your decisions have immediate, measurable impact on millions of users across 70+ countries
• A truly international environment Collaborate with a diverse team of 50+ nationalities across Paris, London, Berlin, New York, Singapore, and Ho Chi Minh City
• Career acceleration in a fast-moving scale‑up Take ownership early, grow fast, and shape your path, as an expert or a future leader
• Learning & growth as a priority Dedicated budget, continuous feedback culture, and opportunities to work on cutting-edge topics (AI, marketplace dynamics, scalability, etc.)
• Flexible ways of working Hybrid model (typically 2 days remote per week), with trust and autonomy at the core of how we operate
• Give back through action 2 paid days per year to support a cause of your choice and actively contribute to positive impact beyond your day‑to‑day role
• Competitive compensation & benefits Including bonus, health coverage, lunch vouchers, Gym‑Pass, and additional legal perks depending on your location

Equal Opportunity Statement

Vestiaire Collective is proud to be an equal opportunity employer.