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Salary: USD 150,000 - 175,000 / annual
K Health, an AI-powered virtual care platform backed by $443.5M in funding, is seeking an experienced Data Engineer to join its data engineering team in New York City.
You will be at the heart of K Health's data ecosystem, designing and executing cross-engineering initiatives that drive decision-making across the organization. Your responsibilities will include:
• Design, develop, and optimize data services and solutions supporting company products like FeatureStore and synthetic data management
• Work closely with data analysts, data scientists, engineers, and cross-functional teams to understand requirements and deliver high-quality solutions
• Design and integrate LLM- and agent-based capabilities into data platforms and services, enabling AI-driven data products
• Design, develop, and optimize scalable data pipelines ensuring data is clean, accurate, and ready for analysis
• Build and maintain robust data models supporting clinical, business intelligence, and operational needs
• Implement and enforce data quality standards, monitoring, and best practices across systems and pipelines
• Manage and optimize large-scale data storage and processing systems for reliability and performance
The role requires onsite presence in the New York City office 4 days per week (Monday–Thursday), with Fridays remote. No immigration support is provided.
K Health's mission is to modernize primary care through AI-powered virtual care. The company offers clinical AI tools (PatientGPT), provider-serving solutions (Perfect Note), and AI-powered virtual clinics deployed across leading health systems.
QUALIFICATIONS:
• 5+ years of experience as a Data Engineer or Backend Engineer with strong emphasis on data processing
• Python proficiency: proven ability to build services, solutions, data pipelines, automations, and integration tools
• SQL expertise: deep experience crafting complex queries, optimizing performance, and working with large datasets
• Strong knowledge of data modeling principles and best practices for relational and dimensional data structures
• Passion for maintaining data quality and ensuring trust in business-critical data
BONUS QUALIFICATIONS:
• Experience with cloud platforms (AWS, GCP, or Azure) for data engineering and storage solutions
• Knowledge of data orchestration tools (e.g., Airflow)
• Understanding of CI/CD practices and version control systems
• Experience with Kubernetes
• Experience in ML/AI development
