As our Data Platform Engineering Lead, you will act as the technical authority for the Salomon Data Platform, setting and enforcing the engineering standards that make it reliable, scalable, cost-efficient and easy to build on.
Own the platform architecture, data models & cost efficiency
- Design and evolve the analytics engineering layer in dbt / Snowflake: modeling standards, layering (staging → core → marts), semantic consistency across domains.
- Define data contracts between producers and consumers and enforce them technically, working closely with Enterprise & Data Architects and Data Governance.
- Own platform FinOps: monitor and optimize Snowflake and Azure consumption, making cost a first-class design criterion.
Set the engineering standard
- Establish and champion best practices: testing, CI/CD for data, code review, version control, observability.
- Own data quality and reliability by design (testing frameworks, freshness and anomaly monitoring, lineage) to keep incidents to a minimum.
- Act as technical reviewer and quality bar for the team's most critical work.
Build the self-service foundation
- Provide the modeled, tested and documented data foundations the semantic / metrics layer is built on, in close alignment with the AI Lead.
- Make the platform something teams can build on without asking permission: clear interfaces, documented primitives, sensible defaults.
Scale the team
- Mentor Data Engineers and Analytics Engineers, raising the technical ceiling of the whole group.
- Lead architecture decisions and technical design reviews, documenting the rationale.
- Partner with the AI / ML Lead so the platform exposes the feature and semantic surfaces their models need.
Connect & anticipate
- Contribute to delivery planning (PI Planning, sprint reviews) and anticipate platform implications of upcoming builds.
- Act as the technical interface to IT and infrastructure stakeholders (SAL IT, Group EDA) on integration and data architecture.
- Bring ideas, flag risks early, and help others deliver better.
You are a strong match for this role if you bring:
- 8 to 10 years in data engineering / analytics engineering, including ownership of platform-level architecture, not only pipeline delivery.
- Deep, hands-on mastery of the modern data stack: Snowflake, dbt, Airflow, Azure.
- Advanced SQL and solid software-engineering fundamentals (testing, CI/CD, modularity, versioning), including medallion architecture.
- Experience with data contracts, data quality and observability frameworks.
- Cloud and data platform cost management (FinOps).
- Experience in multi-market, multi-source enterprise environments.
- Hands-on use of AI tools to accelerate engineering work.
- A proven track record of setting engineering standards a team actually adopts, with mentoring experience.
- Master's or Engineering degree in Computer Science, Data Engineering, Information Systems or an equivalent field (equivalent professional experience accepted).
- Fluent English.
- Location: Annecy
- Contract: CDI
- Team: manages 1 internal Data Engineer, with functional oversight of ~5-7 external delivery partner resources
🚀 Ready to become the technical backbone of Salomon's Data Platform and help teams build with confidence? Apply now and join the adventure.