About Pflegewegweiser
As part of the Entyre Group, Pflegewegweiser is one of the fastest-growing health tech scale-ups in the Swiss market. With offices in Zurich, Berlin, and Boston and more than 500 employees, we are redefining outpatient care: tech-enabled, fast, effective, and close to people. We combine high-quality care with operational excellence, clear processes, and a modern, technology-driven organization.
We believe that every person deserves to live a self-determined, dignified life at home, even when care is needed. Family caregivers provide tremendous support and deserve professional assistance, reliable structures, and genuine appreciation.
About the Role
We're looking for a Marketing Analytics Engineer to own and scale Entyre's marketing data infrastructure. This is a high-impact, high-ownership role at the intersection of data engineering, analytics, and marketing.
You'll design and develop the pipelines that move data from our source systems into our warehouse, transform it into reliable, analysis-ready models, and make it accessible through dashboards and automated workflows used by the marketing team every day.
This isn't a traditional data engineering position. You'll pair deep technical skills with strong marketing domain expertise to create a self-serve data layer that empowers the team to measure outcomes, run experiments, forecast with confidence, and optimize campaign performance.
You'll also explore and apply AI to accelerate analytics workflows, improve data accessibility, and build smarter, more proactive tooling for decision-making.
What You'll Do
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Own and evolve the end-to-end marketing data stack: Fivetran or custom ELT pipelines → BigQuery → Dataform transformations → Sigma reporting
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Design, build, and maintain data models that act as the single source of truth for marketing performance, attribution, and funnel metrics
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Build AI-assisted analytics tools and workflows to reduce manual reporting and accelerate insight generation across the marketing team
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Develop and operationalize forecasting models for marketing spend, pipeline projections, and channel performance
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Partner closely with the CMO to translate business questions into robust, scalable data solutions
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Ensure data quality, integrity, and clear documentation across all marketing data assets
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Evaluate, test and integrate new data sources, tools, and technologies as the stack evolves
