Data Engineer

Description

The company owns luxury brands in jewelry, watches and high-end accessories. Each brand keeps its own heritage and identity, while new products are designed through continuous creative work.

The role sits at the base of the technical setup. You will build and run the data infrastructure and BI reporting behind analytics work, working directly with the operational teams of the MCCs.

You will work within the RIMS Digital Transformation Department, creating ready-to-use data models for other teams, building high-performing infrastructure and dashboards, and supporting AI-related change.

Across infrastructure, business intelligence and AI, you will design the data models that guide day-to-day decisions across the MCCs and RIMS.

Responsibilities

• Build and maintain reports for the MCCs.
• Set up and upkeep Looker dashboards and visuals, turn complex business needs into usable KPIs, and train users to get the most from the platform.
• Design and build data marts, using Git and version control.
• Help build and maintain ETL/ELT pipelines in Airbyte that load SQL tables and flat files into BigQuery reliably.
• Document data lineage so Looker stays the single source of truth.
• Check that models across the MCCs stay consistent, so teams can share work and keep reports running when blockers appear, while protecting report performance.
• Confirm that models deployed by the MCCs run efficiently and stay within Group targets for cost and data consumption.
• Watch the health of the data platform, add integrity checks, fix data quality issues, and apply governance and access controls in line with Group strategy, including Monte-Carlo.
• Act as a key contact for sharing best practice across entities, for the benefit of the Group and the MCCs.
• Serve as the primary contact for developing, evolving and integrating AI solutions in the Group's analytics tools.
• Lead complex projects, manage priorities, and work with IT, manufacturing and business teams.

Requirements

• Master's degree in computer science, data engineering or a related scientific field.
• More than 5 years of experience in data engineering or analytics engineering.
• Expert command of SQL and Looker, including LookML, with experience building sophisticated dashboards and the transformation layers behind them.
• In-depth knowledge of Google Cloud Platform, including BigQuery, and strong habits in development and database management.
• Ability to assess AI tool proposals from the Group, help deploy them within the industrial scope, and ensure their use meets compliance and cybersecurity requirements.
• Comfort working in a dynamic setting, delivering new features quickly for demanding business users under an Agile operating model.

Conditions

If your application is selected, you will have an introductory call. The interview process includes meeting the people who will be key to your success in the role.