CMC Analytics Engineer

SIX is building a dedicated Tech & Data capability within the Marketing & Communications (CMC) department. Its foundation is a marketing data spine on the enterprise Databricks Data Lakehouse: a traceable chain from campaign activity and spend through engagement, leads and opportunities to revenue.

Reporting to the Head Tech & Data Marketing & Communications, the CMC Analytics Engineer owns the transformation layer: the data marts, the identity stitching, the feature pipelines feeding the measurement models, and the semantic layer behind the ROMI and CMC KPIs cockpit.

This is an opportunity for an analytics engineer who wants to shape a domain data product from first principles — with a clean split of responsibilities (ingestion provided as a service), a modern platform, and models and executives as direct customers.

What You Will Do

• Design and build the marketing transformation layer on Databricks: campaign, spend, engagement, opportunity and revenue data marts on the ingested raw data
• Build identity and account stitching: persistent identifiers linking campaigns, contacts, accounts, opportunities and revenue into one measurable spine
• Build and maintain feature pipelines for marketing mix modelling, attribution and personalization models
• Own the semantic layer and certified datasets serving the CMC reporting suite and self-service reporting
• Define data contracts with the IT ingestion service and upstream enterprise data models; implement data-quality monitors against the team's governance standards
• Apply solid engineering practice: Unity Catalog, CI/CD, testing, cost and performance optimisation, documentation
• Support activation use cases — audiences and segments delivered back to the MarTech stack adhering to regulations.

What You Bring

• Strong analytics-engineering craft: advanced SQL and PySpark, dimensional and medallion modelling, dbt-style transformation discipline
• Production experience on Databricks (Unity Catalog, workflows) or a comparable lakehouse platform
• Experience building semantic models and certified datasets
• A data-contract and data-quality mindset: schemas, tests, monitors and clear interfaces to upstream providers
• Ideally, familiarity with marketing and CRM domain data — campaigns, funnels, opportunity data
• The ability to work as an embedded counterpart to external build partners and internal platform teams
• Experience embedding AI agents into business processes and data workflows — agentic pipelines, Genie-style assistants and AI endpoints on the lakehouse

What We Offer

• Hybrid model up to 40% working from home
• Private Medical care and life insurance
• Meal, transportation and electricity allowance
• Sport card
• Cinema tickets, Benefit System points
• Up to 20 days working from abroad / Day for U
• Access to technical and language learning platforms