Data Platform Engineering Lead

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