Staff data engineer

Staff Data Engineer

Location: Fully Remote

Velocity Tech has partnered with an innovative healthcare technology company that is transforming how individuals access, manage, and act on their complete health records. The organization unifies data across health systems, payers, labs, pharmacies, and wearable devices through modern APIs and interoperability standards (FHIR, HL7, CCDA), empowering people to make informed, personalized health decisions.

About the Role

Velocity Tech’s partner is seeking an experienced Staff Data Engineer to help evolve the data and AI foundations that power personalized healthcare at scale. This role focuses on designing and implementing robust, secure, and scalable data pipelines that serve both analytical and operational use cases across a cloud-native environment.

The ideal candidate thrives at the intersection of data engineering, healthcare data, and cloud infrastructure—driving innovation and reliability in complex data ecosystems.

Please note: The client is only considering candidates with professional experience in the healthcare or healthtech industry.

Key Responsibilities

• Design and implement distributed data systems and pipelines for large-scale healthcare applications.
• Develop and maintain real-time and batch data infrastructure integrating multiple healthcare data sources.
• Build and optimize backend services and APIs using FastAPI , MongoDB , and cloud-native technologies.
• Champion technical excellence through code quality, testing, and peer review practices.
• Provide mentorship and technical leadership to data engineers and cross-functional teams.
• Develop and scale event-driven data pipelines leveraging Kafka , Spark , and DuckDB .
• Implement strong observability, monitoring, and alerting for distributed systems.
• Improve internal development workflows, automation, and CI/CD pipelines.
• Ensure compliance, data privacy, and security best practices (HIPAA, HITECH) across all systems.

Qualifications

• 8+ years of software and data engineering experience, including 3+ years with distributed data systems.
• Demonstrated success designing data solutions for complex, high-scale healthcare environments.
• Proficiency in Python and related libraries such as Pandas , PySpark , and FastAPI .
• Experience with data orchestration tools like Prefect or Airflow .
• Familiarity with Docker , Kubernetes , and CI/CD processes.
• Strong collaboration and communication skills, with a proven ability to mentor and guide others.
• Working knowledge of healthcare interoperability standards (FHIR, HL7, CCDA).

Preferred Skills

• Experience deploying or maintaining LLMs, ML models, or retrieval-based data systems.
• Exposure to observability tools such as OpenTelemetry , Datadog , or Prometheus .
• Hands-on experience in healthcare, healthtech, or other regulated data environments.
• Contributions to open-source projects or public repositories.