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Vestiaire Collective is the leading global marketplace for pre-loved fashion, operating across 70+ countries with offices in Paris, London, Berlin, New York, Singapore, and Ho Chi Minh City. The company is reshaping the fashion industry toward circularity and sustainability, with a team of approximately 600 people from over 50 nationalities.
As a Senior Analytics Engineer, you will be embedded within the central Analytics Engineering team and play a key role in the company's data ecosystem. You will design, build, and maintain scalable, high-performance data pipelines and analytical data products that power strategic decision-making across Product, Marketing, CRM, Finance, Operations, and other business areas.
Key responsibilities include:
- Design, build, and maintain scalable data pipelines and reusable analytical data products using dbt, Snowflake, and Airflow
- Transform complex raw data into structured, reliable, and accessible data models with appropriate testing and documentation
- Own analytical data products throughout their lifecycle, from design through delivery, continuous improvement, and retirement, considering performance, maintainability, and cost
- Contribute to the evolution of engineering foundations supporting Analytics Engineering, including CI/CD, orchestration, monitoring, deployment, and tooling upgrades in collaboration with Data Platform Engineering
- Partner with cross-functional teams (Finance, Operations, Commercial, Marketing, CRM, Product) to translate business needs into clear, reliable, and scalable data solutions
- Take ownership of projects from design through delivery and communicate technical decisions and trade-offs clearly
- Explore and apply AI-assisted engineering tools across the data development lifecycle
- Help define and embed Analytics Engineering best practices, fostering a culture of quality, ownership, documentation, testing, and continuous improvement
The role offers purpose-driven work at scale, high-impact scope with ownership, a truly international environment, career acceleration in a fast-moving scale-up, learning and growth as a priority, flexible hybrid working (typically 2 days remote per week), and competitive compensation including bonus, health coverage, lunch vouchers, gym pass, and additional legal perks.
Requirements:
- 3-5 years of relevant experience in Analytics Engineering, Data Engineering, BI Engineering, or similar role, with hands-on experience designing, deploying, and maintaining large-scale, efficient ETL, ELT, or reverse ETL pipelines
- Strong SQL and data transformation skills with dbt, including complex transformations and modular, reusable data models
- Experience with Snowflake, BigQuery, PostgreSQL, or another modern data warehouse, with awareness of performance and cost considerations
- Experience with Airflow or comparable tool for job orchestration, scheduling, and dependency management
- Experience using Python for data processing, workflow automation, or developing data tooling
- Experience with version controlling (GitHub), CI/CD, automated testing, monitoring, and observability
- Ability to work autonomously, manage dependencies, and take accountability for data products and technical initiatives beyond initial delivery
- Ability to make and clearly communicate technical decisions and trade-offs
- Strong communication skills and ability to work effectively with technical and non-technical stakeholders
- Practical experience or strong interest in applying AI-assisted engineering tools to data development
- Strong problem-solving mindset and commitment to engineering quality
- Prior exposure to e-commerce platforms, two-sided marketplaces, or high-volume AdTech ecosystems is a plus
