Senior Analytics Engineer

Company Description

Amer Sports is a sporting goods company with internationally recognized brands including Salomon, Arc’teryx, Peak Performance, Atomic and Wilson.

“The Mountain Sport Company”, Salomon was born in 1947 in the heart of the French Alps and the birthplace of modern alpinism. Salomon’s commitment to innovative design and passion for mountain sports created a vast range of revolutionary new concepts in bindings, boots, skis and apparel for both Alpine and Nordic skiing and brought innovative solutions to footwear, apparel and equipment for snowboarding, adventure racing, mountaineering, hiking, trail running, and many other sports.

Through performance driven design, Salomon delivers innovation and progression to mountain sports; converting new ideas into action and expanding the limits of possibility. Salomon’s heritage, culture, and commitment are tied together by one simple concept: the world’s leading mountain people creating the world’s leading mountain products. Salomon is responsibly committed towards the outdoor through its sustainability program. Diversity is one of Salomon’s five values, therefore we are committed to creating an inclusive environment for all.

Salomon is headquartered in Annecy, France.

Job Description

OVERVIEW

We are seeking a Senior Analytics Engineer to strengthen analytics enablement across our North American eCommerce business. This role focuses on improving the reliability, scalability, and usability of data pipelines and analytics platforms so teams can make faster, better-informed decisions.

Operating in a matrixed global environment, this role requires strong technical judgment, business fluency, and the ability to work autonomously. The Senior Analytics Engineer will act as a connective layer between data infrastructure, analytics delivery, and business stakeholders, ensuring data products are durable, trusted, and adopted.

For the right candidate, this role may also provide functional leadership over insights delivery, helping shape how analysis is executed and consumed across the organization.

ESSENTIAL DUTIES & RESPONSIBILITIES

To perform this job successfully, an individual must be able to perform each essential duty and responsibility satisfactorily:

• Serve as the North American analytics enablement point of view, partnering with Global Data & Analytics teams to inform priorities, requirements, and roadmap decisions
• Design, build, and maintain reliable, scalable data pipelines and transformations that support analytics and reporting use cases across the business
• Develop and enhance dimensional data models and analytics-ready datasets to enable efficient, trusted access to data
• Ensure performance, reliability, and data quality across analytics platforms, including monitoring, testing, and proactive issue prevention
• Perform root cause analysis on data and pipeline issues, implementing durable solutions that reduce recurrence and downstream impact
• Enable scalable analytics and self-service reporting through well-documented datasets, BI tools, and shared standards
• Translate business questions into end-to-end data solutions, delivering actionable insights and recommendations in collaboration with cross-functional and senior stakeholders

Qualifications

QUALIFICATIONS, SKILLS, ABILITIES & COMPETENCIES

The requirements listed below are representative of the knowledge, skill and/or ability required.  Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• 5–7 years of experience in analytics engineering, data engineering, or advanced analytics roles
• Advanced proficiency with SQL for data transformation, modeling, and large-scale dataset manipulation
• Demonstrated experience designing, building, and maintaining production-grade data pipelines using modern ETL/ELT frameworks and orchestration tools (e.g., dbt, Airflow, Databricks)
• Strong hands-on experience with data warehousing concepts, dimensional modeling, and schema design in MPP environments (e.g., Snowflake, Redshift, BigQuery)
• Practical experience using Python or R to support data pipelines, analysis, automation, or quality validation
• Experience enabling scalable analytics platforms and self-service reporting through BI tools such as Tableau, Power BI, or Excel
• Proven ability to translate complex data into actionable insights and recommendations for cross-functional and senior-level business stakeholders

Additional Considerations

• Advanced degree in Data Science, Analytics, Computer Science, or equivalent practical experience
• Fluent or conversational French, with experience working in multilingual or