Data Engineer

Join our Data Engineering team and help shape a strategic data platform based on Snowflake, dbt, and Data Vault. You will design scalable data solutions, integrate data from across the organization, and create trusted, reusable business objects that power analytics, reporting, and data-driven decision-making. If you are passionate about modern data architectures, cloud technologies, and turning complex data into business value, we would love to hear from you.

• Design, build, and maintain robust data pipelines on Snowflake using dbt.
• Develop and enhance Data Vault models, including Hubs, Links, Satellites, and Business Vault components.
• Create reusable business objects and data products that support enterprise-wide reporting, analytics, and regulatory requirements.
• Integrate data from a wide range of source systems into a centralized data platform.
• Apply metadata-driven development principles to increase automation, consistency, and scalability.
• Collaborate with business analysts, architects, and data consumers to understand requirements and translate them into sustainable data solutions.
• Ensure data quality, traceability, lineage, and governance across the entire data lifecycle.
• Optimize data models and transformations for performance, maintainability, and cost efficiency.
• Contribute to CI/CD pipelines, automated testing, and Data Ops practices.
• Participate in the continuous improvement of data engineering standards, frameworks, and development methodologies.
• Work at the core of the data platform, define patterns and best practices and act as a enabler in a multi team setup, sharing knowledge and raising the efficiency of other team-members with your contributions.

• Bachelor’s or master’s degree in computer science, engineering, information systems, or a related discipline.
• Proven experience as a data engineer, analytics engineer, or in a similar role.
• SQL expert who thrives in complex data landscapes, creating elegant, highly efficient, and maintainable data flows.
• Deep understanding of data historization principles (and pitfalls), including business, technical, and load-time timelines, bi-temporal and multi-temporal modeling, and related algorithms.
• Good knowledge of Data Vault and dimensional modelling principles and enterprise data warehousing concepts.
• Thorough experience with dbt, including model development and testing, and topics like sim ci, custom materializations and macros.
• Hands-on project experience with pandas and data frame based processing, complemented by Snowpark expertise in building scalable data transformations and analytical workflows.
• Experience with modern cloud-based data platform architectures (e.g. Snowflake, Data Bricks, etc.).
• Familiarity with git-based development workflows, modern data engineering practices, including CI/CD and automated data testing.
• Practical software development and architecture in languages such as C# or Rust is a plus.
• Experience in data quality management, data governance, and metadata management.
• Strong analytical thinking and problem-solving abilities.
• Good communication skills and the ability to work effectively with technical and business stakeholders.
• Affinity for Artificial Intelligence (AI) and a willingness to embrace AI-enabled tools and ways of working.

• Top Zurich location with collaboration spaces and free lunch.
• Friendly, diverse team in an open-office space.
• All the latest technology to help you excel and advance.
• Agile environment in how we think, the way we work and our trust for each other.
• Flat hierarchy with collaboration at all levels.
• Campus feeling and a collaborative spirit.

This role is based in Zurich but will move to Baar in 2030, ensuring close…