Data Engineer

The Role

As a Data Engineer at Circadia Health, you will play a critical role in building and maintaining the data infrastructure that powers Circadia’s AI-driven clinical monitoring platform. You will design and operate robust data pipelines that ingest, transform, and distribute sensitive healthcare data originating from Electronic Health Record (EHR) systems, medical devices, and hospital information systems.
Reporting directly to the Lead AI Engineer, you will work closely with backend engineers, ML engineers, clinical teams, and customer integration partners to ensure reliable, secure, and compliant flow of patient data — including ADT events, conditions, medications, allergies, clinical notes, and vital signs.
Your work will directly enable Circadia’s predictive analytics and machine learning models that identify early signs of clinical deterioration, helping clinicians intervene sooner and improve patient outcomes. This is a hands-on role where production-grade data engineering, reliability, and healthcare compliance are non-negotiable.

What You'll Do

Data Pipeline & Integration Development
Design, build, and maintain scalable data pipelines to ingest healthcare data from customer EHR systems and hospital databases.
Develop integrations using:
REST APIs and webhook-driven workflows
Database log shipping and change data capture (CDC) mechanisms, including Microsoft SQL Server–based systems
Transform, validate, and normalize incoming clinical data before loading it into Circadia’s MySQL and Snowflake environments.
Ensure pipelines are robust, fault-tolerant, and capable of handling large data volumes.
Healthcare Data & EHR Integrations
Integrate and manage healthcare data domains including:
Admissions, Discharges, Transfers (ADT)
Conditions, medications, allergies
Clinical notes and progress notes
Vital signs and physiological measurements
Work with healthcare interoperability standards and protocols such as:
HL7 v2
FHIR
Partner with customer technical teams to support onboarding, troubleshooting, and ongoing data reliability.
Data Platforms & Warehousing
Take ownership of Circadia’s operational databases and analytical data warehouses.
Design schemas and transformations that support both real-time application needs and downstream analytics and ML workloads.
Optimize performance, cost, and scalability within Snowflake and MySQL.
Cloud Deployment & Operations
Deploy and operate data pipelines and services in AWS.
Implement monitoring, logging, alerting, and operational dashboards for data workflows.
Support production reliability, incident response, and continuous improvement of data systems.
Security, Compliance & Data Quality
Ensure all data pipelines meet healthcare security and privacy requirements, including HIPAA and SoC 2.
Apply best practices for handling Protected Health Information (PHI), including access control, encryption, and audit logging.
Maintain clear documentation of data flows, transformations, and operational processes.
Collaboration & Enablement
Work closely with Data Science and ML teams to support:
Model training and evaluation
Feature generation and data labeling workflows
Collaborate with backend engineers to develop internal tooling for data ingestion, validation, and monitoring.
Participate in architecture discussions to ensure data systems scale with Circadia’s growth.

Must‑Have Qualifications

• 5+ years of experience in Data Engineering, Backend Engineering, or a closely related role.
• Strong proficiency in Python for data pipeline and backend development.
• Strong proficiency in SQL.
• Hands-on experience with MySQL and Snowflake, including schema design and performance optimization.
• Experience integrating data from Microsoft SQL Server, including log shipping or CDC-style approaches.
• Experience building high-throughput data pipelines from ingestion through transformation and storage.
• Experience deploying and operating production systems in a major cloud provider (AWS preferred).
• Familiarity with APIs, webhooks, and event-driven architectures.
• Experience working with sensitive or regulated data.

Nice‑to‑Haves

• Experience integrating with EHR systems (e.g., Epic, Homecare Homease, PointClickCare).
• Familiarity with healthcare data standards such as HL7 and FHIR.
• Experience supporting machine learning or data science teams.
• Experience with data orchestration, workflow management, or streaming systems.
• Background in healthcare, medical devices, or clinical data systems.
• Exposure to HIPAA compliance and healthcare security best practices.