Privacy Engineer
Overview
An early-stage health technology company, founded in 2020 by leaders in health tech, hospital systems, academia, and clinical AI, is building a large-scale clinical data platform to accelerate innovation across life sciences and AI-driven healthcare. The organization focuses on making high-quality clinical data accessible while maintaining rigorous standards for patient safety, privacy, and data integrity. The team operates in a culture centered on continuous learning, data-driven improvement, and responsible AI development.
The Data Platform
The company partners with major U.S. health systems to securely and ethically provide de-identified patient data to AI developers and life sciences organizations. The platform includes longitudinal clinical data dating back to 2016 and represents over 10 million patients. Data types include structured records, unstructured clinical text, medical imaging, video, physiological waveforms, and select non-health system datasets matched using tokenized encryption keys.
The technical stack is primarily Python-based and cloud-native, with data stored and processed using modern data warehouses and columnar file formats in a cloud environment.
The Role
Patient privacy is a core priority, and privacy-preserving workflows are critical to the platform. This role focuses on building and operating scalable de-identification systems that remove or mask protected health information (PHI) across large, complex datasets. Responsibilities include:
• Collaborating with privacy leadership and clinical experts to define detailed de-identification rules across structured data, text, images, and signals
• Developing software to apply de-identification logic at scale, processing billions of records and millions of images monthly
• Designing and executing quality assurance processes to validate privacy safeguards
• Operating and optimizing de-identification pipelines in cloud environments to improve accuracy, efficiency, and cost effectiveness
Required Technical Qualifications
• 2+ years of professional software development experience in Python or a comparable language
• Experience across the full software development lifecycle
• Working knowledge of SQL and command-line tools (e.g., Bash)
Required Professional Skills
• Ability to design, document, and improve operational workflows and QA processes
• Strong analytical judgment and organizational skills
• Practical problem-solving mindset and persistence
• Collaborative, humble approach to teamwork
• Genuine interest in protecting sensitive patient data
Preferred Qualifications
• Experience working with large datasets and data structures such as Pandas DataFrames
• Prior deployment of software in cloud environments (e.g., AWS, Azure)
• Familiarity with containerization or virtualization tools
• Exposure to healthcare or clinical data
• Experience partnering with non-technical stakeholders to implement software solutions
Apply Now
Apply Now
An early-stage health technology company, founded in 2020 by leaders in health tech, hospital systems, academia, and clinical AI, is building a large-scale clinical data platform to accelerate innovation across life sciences and AI-driven healthcare. The organization focuses on making high-quality clinical data accessible while maintaining rigorous standards for patient safety, privacy, and data integrity. The team operates in a culture centered on continuous learning, data-driven improvement, and responsible AI development.
The Data Platform
The company partners with major U.S. health systems to securely and ethically provide de-identified patient data to AI developers and life sciences organizations. The platform includes longitudinal clinical data dating back to 2016 and represents over 10 million patients. Data types include structured records, unstructured clinical text, medical imaging, video, physiological waveforms, and select non-health system datasets matched using tokenized encryption keys.
The technical stack is primarily Python-based and cloud-native, with data stored and processed using modern data warehouses and columnar file formats in a cloud environment.
The Role
Patient privacy is a core priority, and privacy-preserving workflows are critical to the platform. This role focuses on building and operating scalable de-identification systems that remove or mask protected health information (PHI) across large, complex datasets. Responsibilities include:
• Collaborating with privacy leadership and clinical experts to define detailed de-identification rules across structured data, text, images, and signals
• Developing software to apply de-identification logic at scale, processing billions of records and millions of images monthly
• Designing and executing quality assurance processes to validate privacy safeguards
• Operating and optimizing de-identification pipelines in cloud environments to improve accuracy, efficiency, and cost effectiveness
Required Technical Qualifications
• 2+ years of professional software development experience in Python or a comparable language
• Experience across the full software development lifecycle
• Working knowledge of SQL and command-line tools (e.g., Bash)
Required Professional Skills
• Ability to design, document, and improve operational workflows and QA processes
• Strong analytical judgment and organizational skills
• Practical problem-solving mindset and persistence
• Collaborative, humble approach to teamwork
• Genuine interest in protecting sensitive patient data
Preferred Qualifications
• Experience working with large datasets and data structures such as Pandas DataFrames
• Prior deployment of software in cloud environments (e.g., AWS, Azure)
• Familiarity with containerization or virtualization tools
• Exposure to healthcare or clinical data
• Experience partnering with non-technical stakeholders to implement software solutions
Apply Now
Apply Now