Data Engineer

A mission-driven Israeli health-tech startup builds a smart, digital, and affordable HMO in the US. The company develops a comprehensive healthcare solution that combines medical services and health insurance, focusing on reducing healthcare costs through proactive member health management. The digital platform enables members to manage their health via video calls, prescriptions, and lab result tracking, while the team analyzes large volumes of health data to uncover patterns and trends for preventive care strategies.

• Build and operate end-to-end data pipelines (batch & streaming);
• Design the data platform including warehouse/lake, orchestration, and transformations;
• Own the implementation of the semantic layer and metric definitions to establish 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.

• 7+ Years in data engineering or analytics engineering;
• Strong proficiency in SQL (including advanced queries) and Python (including Pandas);
• Proven experience with modern data stack technologies such as Airflow, DBT, or Spark;
• Experience with cloud data warehouses like 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;
• Passionate about data exploration, uncovering patterns, identifying anomalies, and generating business insights;
• Excellent communication skills in English for collaboration across international teams;
• Nice to have: Experience with BigQuery, exposure to data observability, data quality frameworks, monitoring solutions, familiarity with AI/ML data pipelines, experience with complex domains like healthcare, FHIR, or ontologies.

• No conditions specified