Analytics Engineer

We are looking for an experienced Analytics Engineer to join our Clinical Value team and develop the data foundations, infrastructure, and analytical tools that enable our work.
This hybrid role combines Analytics Engineering with hands-on data analysis. You will translate complex analytical and clinical needs into scalable, reliable, and reusable data solutions.
You will design data models, pipelines, analytical layers, and tools that enable complex Clinical Value studies across products and customers, while remaining hands-on with selected analytical projects.
You are expected to be independent, proactive, and impact-oriented, taking end-to-end ownership of technical challenges and opportunities for improvement.
evaluation.
Responsibilities:
Design, build, and maintain the data infrastructure supporting Clinical Value analyses, including reusable data models, pipelines, analytical layers, and tools.
Own the technical and analytical implementation of complex Clinical Value applicati

דרישות:

Education & Experience: B.Sc. or higher in a Scientific or Engineering discipline with 3+ years of experience in Analytics Engineering, Data Engineering, or a technical analytics role.
Core Technical Stack: Advanced Python and SQL skills; hands-on experience designing and building production data models, pipelines, and analytical layers.
Tools & Platforms: Experience with orchestration/transformation tools (DBT, Airflow, or similar) and cloud data platforms (Databricks, Snowflake, BigQuery, or AWS).
Engineering Standards: Strong understanding of data modeling, data quality, testing, and maintainability best practices.
AI Tooling & Automation: Hands-on experience integrating AI development tools and agents (e.g., Cursor, Claude agents, GitHub Copilot) into daily workflows to accelerate coding, debugging, and pipeline development.
Data Analysis Capabilities: Strong analytical mindset with the ability to independently explore and analyze complex datasets, summarize findings, and extract