Data Engineer

A mission-driven Israeli health-tech startup is working to build a smart, digital, and affordable HMO in the US. The company is developing a comprehensive healthcare solution that combines both medical services and health insurance, with a strong focus on reducing healthcare costs through proactive member health management. Their digital platform allows members to manage their health easily — from video calls with doctors and receiving prescriptions and referrals via the app, to tracking lab results and much more. The goal is to empower users with personalized insights that support healthier lifestyles and help prevent medical issues before they arise. A major focus of their work involves analyzing large volumes of health data to uncover patterns and trends that can guide preventive care strategies. By effectively leveraging this data, they aim to provide members with the tools to better understand and manage their long-term well-being. We are currently looking for a Senior Data Engineer to own the design and implementation of a scalable, trusted data platform powering analytics and AI. What You’ll Do Build and operate end-to-end data pipelines (batch & streaming) Design the data platform (warehouse/lake, orchestration, transformations) Own the implementation of the semantic layer and metric definitions, establishing a single source of truth Ensure data quality, reliability, and performance at scale Partner with Product and Data teams to deliver impactful data solutions Enable AI/ML use cases with high-quality, well-structured data Requirements: 7+ years in data engineering / analytics engineering Strong proficiency in SQL (incl. advanced queries) and Python (incl. Pandas) Proven experience with modern data stack technologies (e.g. such as Airflow, DBT, Spark) and cloud data warehouses (BigQuery, Snowflake, or Redshift). Demonstrated ability to design, develop, and maintain scalable, reliable, and high-performance data platforms, pipelines, and ETL/ELT processes. Solid experience with cloud environments, particularly GCP, leveraging native services for secure, serverless, and scalable data ingestion, transformation, orchestration, and analytics Strong understanding of data modeling principles, data governance, and metric ownership, with a focus on delivering trusted and actionable datasets. Passionate about data exploration, with a natural curiosity for uncovering patterns, identifying anomalies, and generating meaningful business insights from complex datasets. Excellent communication skills in English, with experience collaborating across international teams and fast-paced startup environments. Nice to have: Experience with BigQuery Exposure to data observability, data quality frameworks, and monitoring solutions. Familiarity with AI/ML data pipelines and analytics use cases. Experience with complex domains (e.g., healthcare, FHIR, ontologies)