Sr. Data Engineer

Company Description Regal Intel is focused on connecting advanced technology with real-world clinical practice so that no patient remains undiagnosed due to data scarcity. The organization addresses the “Small N” paradox, where standard AI fails on rare, complex, and fast-progressing (“avid”) diseases because traditional models cannot learn from limited data. Through Project JANUS, Regal Intel uses Sovereign Neuro-Symbolic AI and high-fidelity synthetic patient twins to convert fragmented real-world data into regulatory-grade clinical evidence while constraining models with established medical rules. Its hardware-attested federated learning infrastructure ensures zero-exfiltration of protected health information, maintaining full data sovereignty for hospitals. As a mission-driven, non-profit entity, Regal Intel is dedicated exclusively to clinical discovery and patient outcomes, particularly for families in rural health networks.
Role Description The Sr. Data Engineer will design, build, and maintain scalable data pipelines that support Regal Intel’s neuro-symbolic AI platforms and clinical research initiatives. In this full-time remote role, the individual will work closely with data scientists, clinical researchers, and software engineers to integrate diverse healthcare data sources, optimize data workflows, and ensure data quality and reliability. Daily responsibilities include developing and managing ETL processes, modeling and warehousing clinical and operational data, and enabling robust analytics and reporting across federated environments. The Sr. Data Engineer will also contribute to data architecture decisions, documentation, and best practices that align with strict privacy, security, and regulatory requirements.
Qualifications
Strong data engineering skills, including experience with building and orchestrating scalable data pipelines and distributed data processing systems.
Proficiency in data modeling and database design for analytical and operational workloads, with an emphasis on healthcare or similarly complex domains.
Hands-on experience with Extract Transform Load (ETL) development, data integration from multiple sources, and automation of ingestion workflows.
Background in data warehousing and data lake architectures, including performance optimization and governance of large datasets.
Ability to support data analytics initiatives by preparing clean, well-structured datasets and collaborating with analytics and AI teams.
Excellent experience with SQL and at least one programming language commonly used in data engineering (e.g., Python, Scala, or Java).
Familiarity with cloud or hybrid data platforms, federated data environments, and privacy-preserving technologies is highly beneficial.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field, or equivalent practical experience.
Strong communication skills, ability to work independently in a remote setting, and interest in mission-driven work improving patient outcomes.

Work arrangement
Yes