Associate Analytics Engineer

Richemont, one of the world leaders in the luxury sector, has various Houses specializing in jewelry, watches and high-end accessories. Each Maison proudly embodies a tradition of style, quality and craftsmanship and Richemont strives to preserve the heritage and identity specific to each of them. At the same time, we are committed to innovating and designing new products in line with the values ​​of our Houses, through a process of permanent creativity.

At Richemont Americas, we aspire to reflect the ever-changing world around us. We are proud to employ talent from many different backgrounds, experiences, and identities to build a continually evolving, inclusive community where the diversity of our colleagues and clients is rich and celebrated. We believe when inclusion is fully embraced and empowered, creativity and knowledge emerge to deliver excellence, advancing the community that is uniquely Richemont Americas.

Associate Analytics Engineer

Richemont | New York City, NY

Reports to: Senior Manager, Regional Analytics

Role Overview

The Analytics Engineer bridges data engineering and business analytics, transforming complex data into reliable, scalable, and business-ready data products. The role owns the end-to-end development of regional analytics solutions, from understanding business requirements and navigating source data through data modeling, testing, deployment, visualization, and ongoing optimization.

Working closely with regional Markets, Maisons, HQ, and technical teams, the Analytics Engineer enables data-driven decision-making across Client, Finance, Customer Service, with particular responsibility for supporting evolving regional needs across markets including Canada, Mexico, and Brazil.

Responsibilities

Analytics Engineering & Data Product Development

• Design, build, test, document, and maintain scalable data models and analytics products supporting regional business use cases across Client, Finance, Customer Service, Supply Chain but not limited to.
• Own the end-to-end delivery lifecycle of analytics products, translating business requirements into robust technical solutions and driving use cases from initial scoping through development, validation, deployment, adoption, and ongoing maintenance.
• Develop and maintain transformation models using dbt and Airflow, applying appropriate modeling methodologies, reusable logic, testing, documentation, naming conventions, and engineering best practices.
• Build and maintain analytics experiences in Looker, including LookML models, Explores, dashboards, and reporting solutions, ensuring consistency between underlying data models and business-facing metrics.

Data Quality, Governance & Reliability

• Ensure regional analytics products provide accurate, consistent, timely, and trusted data by implementing appropriate validation, testing, monitoring, and documentation practices.
• Investigate data discrepancies and collaborate with local, regional, and central teams to identify root causes and implement sustainable solutions rather than manual workarounds.
• Maintain a strong understanding of the broader data landscape across regional teams, Maisons, HQ, and BIO, identifying the appropriate data assets, documentation, resources, and points of contact when resolving issues.

Business Partnership & Analytics Enablement

• Partner proactively with business stakeholders to understand challenges, clarify requirements, and translate business questions into scalable data models and analytics products.
• Serve as a key regional data partner for designated markets, functions, and Maisons, providing reliable technical and analytical guidance and helping stakeholders make effective use of available data.
• Support regional use cases across Canada, Mexico, and Brazil, together with additional markets and business domains as priorities evolve.

Operational Support

• Ensure the continuity, performance, accuracy, and relevance of existing dashboards and recurring reporting solutions through appropriate maintenance and enhancement.
• Support prioritized ad hoc requests while identifying opportunities to convert recurring manual analyses into automated, reusable, and scalable data products.

Qualifications

Education

• Bachelor's degree in Computer Science, Data Engineering, Data Science, Statistics, Mathematics, Information Systems, or a related quantitative field.
• Master's degree is a plus.

Experience

• 3+ years of experience in analytics engineering, data engineering, business intelligence, data analytics, or a comparable data-focused role.
• Demonstrated experience developing data models and analytics products from business requirements through production deployment.
• Experience working with complex datasets and translating business requirements into maintainable technical solutions.
• Experience partnering directly with both technical and non-technical stakeholders in a cross-functional environment.

Technical Skills

Required or strongly preferred:

• Strong proficiency in SQL and experience working with cloud data warehouses, preferably Google BigQuery.
• Hands-on experience with dbt for data transformation, modeling, testing, and documentation.
• Strong knowledge of Looker, including LookML, data modeling, Explores, and dashboard development.
• Working knowledge of Git/GitLab and modern version-control and code-review practices.
• Understanding of data-modeling principles, data quality, testing, documentation, and analytics engineering best practices.

Preferred:

• Experience with for workflow orchestration.
• Experience with data observability solutions such as Monte Carlo and data-catalog capabilities.
• Familiarity with Python or another programming language used for data processing or automation.
• Experience working within cloud-based analytics ecosystems and shared or federated data environments.

Professional Competencies

• Strong analytical and problem-solving skills with the ability to investigate complex data issues and identify sustainable solutions.
• Strong ownership mindset with the ability to independently drive a data use case from business problem through production delivery.
• Ability to balance technical excellence, business value, scalability, and delivery speed.
• Strong communication skills and the ability to explain complex data and technical concepts to non-technical audiences.
• Proactive and persistent approach to resolving dependencies and blockers.
• Ability to collaborate effectively across regional Markets, Maisons, HQ, business functions, and technical teams.
• High attention to detail and commitment to data accuracy, documentation, and maintainability.
• Ability and willingness to continuously learn and adopt evolving technologies and analytics-engineering practices.

Richemont offers a generous compensation and benefits package for eligible employees. Only candidates selected for further consideration will be contacted.

We Offer – United States

Employee wellbeing is a top priority at Richemont. We offer a comprehensive benefits program to support employees and their loved ones. Our core benefits include medical, dental, and vision programs. Health savings and flexible spending accounts are also available. The company offers income protection solutions including life insurance, disability benefits, and 401(k) with employer match. Understanding the importance of work-life balance, our total rewards include paid time off, a wellness reimbursement benefit, and access to the employee assistance program. Employees are encouraged to make a difference in their local communities with volunteer days off, supporting initiatives that drive change.

At Richemont, We Craft the Future!

Expected Salary Range: $95,000 – 105,000

Salary will be determined based on relevant skills and experience.

#Richemont #WeCraftTheFuture

Access our world of opportunities

In our Group, you can start anywhere and go everywhere. Internal mobility is one of the best growth accelerators to develop within Richemont and our Maisons. We encourage our people to be curious, drive their own career, and dream big.​