Software Engineer, Data Integration
Bayesian Health, Inc.2 months ago
Remote, United StatesMid Level
Responsibilities
- Design and implement data integration interfaces and ingestion pipelines that deliver real-time clinical data to the Bayesian platform.
- Build automated integration tests and investigate and resolve integration and data correctness issues with client technical teams.
- Execute production deployments and serve as the technical point of contact for data integration issues during go-live.
- Develop integration frameworks, tooling, and automation, including leveraging LLMs to improve platform integration velocity.
- Collaborate with Implementation Leads, Clinical Integration, client technical teams, and internal cross-functional stakeholders.
Requirements
- BS in Computer Science or equivalent practical experience.
- At least 3 years of experience building and deploying production data pipelines, including integrations with external APIs; Python is preferred.
- Ability to investigate and resolve data correctness problems end-to-end across services, storage, and external data sources.
- Production experience with cloud solutions such as AWS or Azure and relational databases such as PostgreSQL or MySQL.
- Experience writing automated integration tests for production systems.
- Strong communication and cross-functional collaboration skills.
- Preferred: experience with health data, EHR systems, HL7v2, FHIR, production deployments, go-live or support rotations, production issue triage, enterprise customers, and internal tooling or LLM-based automation.
Tech Stack
Categories
Data Engineering
About Bayesian Health, Inc.
Bayesian Health builds a real-time clinical intelligence platform that integrates with EHRs to detect patient deterioration and surface actionable guidance for clinicians. It sells enterprise software and services to hospitals and health systems, focusing on clinical decision support and workflow integration. The company is privately held and headquartered in New York City, and its platform emphasizes EMR interoperability and deployment across key inpatient use cases.