3 data analyst jobs found in Zürich

Limited to 1 year with option to extend Your tasks Your focus is on the technical design and performance tuning of our data warehouse. You will analyze and optimize our existing data pipelines based on MSSQL. You are responsible for the operation and monitoring of data flows as well as the expansion of monitoring capabilities (peak loads, data accesses, permissions, etc.) and maintain the technical documentation. Your responsibilities include connecting source data and optimizing ETL processes. You enable data usage by connecting and providing APIs. In addition, you will be responsible for implementing CI/CD pipelines, DevOps processes, and data-based tests to ensure data quality. Your responsibilities also include evaluating and implementing data protection-compliant tools, including AI-supported ones, for building, optimizing and monitoring the data warehouse. Your profile Completed higher education in computer science, medical informatics, data...

For over 10 years at Imnoo at Imnoo, we are bridging the gap between applied artificial intelligence and heavy industrial machinery. We aren't just riding the recent AI wave, we have been deeply rooted in machine learning and statistical analysis for 10 years, delivering real, measurable value to a stable, loyal client base of manufacturers. Imnoo is a leading SaaS platform built to analyze CNC parts, automate quoting and planning, and seamlessly connect the cloud with real manufacturers and shop-floor machines. We are looking for a unique hybrid—a CAD AI IoT Engineer / Tinkerer—who thrives at the intersection of software architecture and physical hardware. You won't just be writing code behind a desk; you will be the mastermind connecting our battle-tested algorithms directly to the pulse of the factory floor. If you love reverse-engineering industrial protocols, building edge data pipelines, and parsing complex 3D geometry to automate the business of manufacturing, this...

The team you will join, Proteus, is building a product that powers the model-based work of our internal sector experts: scientists and domain specialists who understand environmental data deeply but are not software engineers. Your job is to build the tooling they use, mentor them in software practice, and help them own production end-to-end. This is hands-on engineering work with a coaching element. You will write production-quality Python, build and maintain data pipelines, collect requirements from domain experts directly, and help people who are not from a software background ship work they can be proud of. This is not a role where requirements land neatly in a ticket and you implement them in isolation. It is not a heads-down engineering position with no stakeholder interaction. If you prefer a fully defined process and minimal ambiguity, this will not work for you. What you will be working on Design and build Python tooling that sector experts use to implement...