Company Overview:

Transforming the way individuals' access and manage their healthcare by offering personalized, convenient, and affordable solutions. Through partnerships with various organizations, consumers are empowered to make informed decisions about their health using a data platform and mobile applications.

The Principal Data Engineer will play a critical role in designing, building, and maintaining advanced data systems and pipelines that integrate a variety of healthcare data sources. The engineer will ensure the platform is scalable and capable of supporting a large user base while centralizing vital health information.

This is a full-time, remote position.

What You'll Do:

• Design, architect, and maintain a cutting-edge healthcare data platform using modern technologies like Python, Databricks, Spark, Prefect, and Kubernetes.
• Collaborate with data engineering teams to enhance platform capabilities, enabling fast, scalable data pipelines for millions of users. Lead the architecture and product development strategy, influencing technical decisions across teams.
• Independently design prototypes to shape future infrastructure improvements and provide technical leadership on core services. Manage project timelines, resources, and dependencies, driving key technology decisions and initiatives that impact multiple divisions.
• Advocate for data technologies to unlock business value and drive efficiency across the organization and its partners.

Job Requirements:

• 10+ years of programming experience, with strong proficiency in Python and 5+ years in data engineering, specializing in Spark or similar distributed frameworks.
• 5+ years of experience in the healthcare sector and 2+ years with cloud-based platforms like Databricks, Snowflake, or similar data lakes.
• Expertise in cloud-native architectures, real-time data streaming, and applying unit testing and test-driven development principles.
• Proven leadership in mentoring engineers and designing scalable data architectures supporting large-scale workloads.

Great to Have:

• Proficient in using orchestration tools (e.g., Airflow, Prefect) and cloud-based data lake technologies (e.g., Databricks).
• Expertise in event-driven architectures with Kafka or similar streaming platforms and API design/integration best practices.
• Experience thriving in fast-paced, dynamic startup environments.