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About the Role
The Data Engineer- Snowflake role requires a strong hands-on background in modern data engineering, specifically within Snowflake and dbt, with experience working in Azure environments. The ideal candidate should be proficient in advanced SQL and Python, comfortable building and maintaining production-grade ELT/data pipelines, and able to work autonomously across data modelling, orchestration, monitoring and troubleshooting.
Responsibilities
- Design, develop and maintain dbt models, tests and documentation, applying strong data quality and modelling practices.
- Apply Git, CI/CD and engineering best practices to ensure maintainable, testable and reliable data products.
- Collaborate effectively with client teams, architects, analysts and external partners in an international environment.
- Demonstrate deep knowledge of the data engineering domain to build, maintain and support robust batch and scheduled data pipelines in production environments.
- Build reliable, fault-tolerant and observable data pipelines with appropriate monitoring, testing and recovery mechanisms.
- Take ownership of complex data engineering workstreams and drive implementation from technical design through production support.
- Develop and maintain documentation relating to all assigned systems and projects.
- Optimise Snowflake queries and data models for performance, scalability and cost across large datasets.
- Perform root cause analysis to identify permanent resolutions to software or business process issues.
Requirements
- Strong dbt experience: model development, testing, documentation, dependency management and deployment practices.
- Strong hands-on Snowflake experience in production environments, including performance optimisation and troubleshooting.
- Advanced SQL skills and strong understanding of data modelling and layered data architectures.
- Python experience for data ingestion, transformation, automation and API integration.
- Experience building, maintaining, monitoring and troubleshooting production ELT/data pipelines.
- Experience with Azure and cloud data services; ability to work comfortably across cloud-based data platforms.
- Good understanding of Git, CI/CD and software engineering practices applied to data engineering.
- Ability to work autonomously, investigate production issues and communicate clearly with technical and non-technical stakeholders.
- Professional English and experience working in collaborative, international teams.
Skills
- Snowflake
- dbt
- Azure
- SQL
- Python
- Git
- CI/CD
- ELT/data pipelines
- Data modelling
- Orchestration
- Monitoring
- Troubleshooting
- Agentic AI
- Dagster
- Airflow
- Terraform
- Snowflake Cortex
- AWS
- S3
- RDS
- Secrets Manager
- CloudWatch
- Kafka
- Power BI
Location
- Paris, France
Work Type
- Permanent
- Remote
- Hybrid
Benefits
- Flexibility, with remote and hybrid work options (country-dependent)
- Career advancement, with international mobility and professional development programs
- Learning and development, with access to cutting-edge tools, training and industry experts
About the Company
- Valtech is the experience innovation company that exists to unlock a better way to experience the world.
- By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.
- At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.
- At Valtech, we don’t just talk about transformation. We make it happen.
- Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.
Equal Opportunity
- We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.
- As per the AGG (General Equal Treatment Act) in Germany and equivalent in France, jobs must be advertised in a gender-neutral manner. We use the statement (all genders) to make it clear that this position is open to all genders in these countries, even if the job title itself can be translated or interpreted as "masculine" in the French or German language.