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noimos is a Zurich-based, but globally focused, start-up harnessing the potential of ML, computer vision, and design to shake up the insurance industry and revolutionize the all-important claims process.

We are an independent subsidiary of one of the largest insurance groups in the world, AXA, and enjoy many of the benefits that come along with it.

noimos is a small group of experienced professionals with strong backgrounds in technology, entrepreneurship, and insurance. We are passionate about making a difference with our products and enjoying ourselves along the way.

The challenges we tackle at noimos are diverse, demanding, and meaningful.

We are looking for an experienced specialist who is able to make decisions independently. The tasks consist of developing innovative approaches to simplify and optimise existing processes. In your new position, you:

• analyze and understand our current data setup, including GCP Workflows, Python, and BigQuery.
• design and implement data architecture and ingestion pipelines.
• work with event-driven architecture and PubSub.
• analyze ML model inputs and outputs, and assist in testing ML models.
• conduct live data analysis and use findings to build features in a data-driven manner.
• collaborate with the ML team to determine optimal data for model performance.
• provide insights into our data and help the business understand it.

• At least 3 years of experience as a Data Engineer or in a similar role, as well as a bachelor's degree in Computer Science, Engineering, or a related field.
• Expertise in SQL and BigQuery, with a deep understanding of data querying and management.
• Hands-on experience with Terraflow and GCP Workflows (or AWS and Azure) for seamless data processing and cloud-based data solutions.
• Proficiency in programming (C#, JavaScript, Python or similar), enabling robust data solutions.
• Familiarity with dashboarding tools (e.g. Looker Data Studio), experience with dbt or Grafana are a plus.
• Solid understanding of data architecture and design principles to build efficient data systems.
• Strong analytical and problem-solving skills and the ability to communicate complex data concepts internally to non-technical stakeholders.
• Fluency in English, both spoken and written, is essential. Proficiency in additional languages is a plus.