[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![Bayesian Health logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/08/f74593d8-221.png)](https://jobicy.com/company/bayesian-health.md)Remote opportunity at[Bayesian Health](https://jobicy.com/company/bayesian-health.md) # Software Engineer, Data Integration Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/bayesian-health.md)Share8 Sep 2026Published23Listing views1Application actions8 Oct 2026Apply before Opportunity details ## About this role. AI SummaryBayesian Health is hiring a Software Engineer to build and operate real-time clinical data integrations between EHR systems and its healthcare platform. The role centers on Python-based ingestion pipelines, external APIs, relational databases, cloud infrastructure, automated integration testing, and production troubleshooting. The engineer will work directly with hospital technical teams during implementation and go-live periods, tracing issues through HL7 messages, mapping, parsing, and ingestion. Preferred experience includes EHR interoperability standards such as HL7v2 and FHIR, enterprise customer delivery, on-call production support, and automation using LLMs. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a technically demanding production-integration role involving complex healthcare data flows, customer-facing incident diagnosis, and high-stakes go-live support. Success requires rapid end-to-end debugging across external EHR systems, data pipelines, mappings, cloud services, and internal platform components. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$145,000US market range$120k–$175k0$193k AI insightNo salary was disclosed in the posting. Estimated US-market annual base salary for a mid-level Software Engineer focused on healthcare data integration, production pipelines, and EHR interoperability is approximately $120,000-$175,000 USD, with an estimated midpoint of $145,000 USD; actual pay may vary by location, depth of HL7/FHIR expertise, and equity or bonus structure. ## Core skills Skills and capabilities most closely associated with this opportunity. [Python](https://jobicy.com/jobs?search_keywords=Python.md)[Data Pipelines](https://jobicy.com/jobs?search_keywords=Data%20Pipelines.md)[EHR Integration](https://jobicy.com/jobs?search_keywords=EHR%20Integration.md)[HL7v2](https://jobicy.com/jobs?search_keywords=HL7v2.md)[FHIR](https://jobicy.com/jobs?search_keywords=FHIR.md)[API Integration](https://jobicy.com/jobs?search_keywords=API%20Integration.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Azure](https://jobicy.com/jobs?search_keywords=Azure.md)[PostgreSQL](https://jobicy.com/jobs?search_keywords=PostgreSQL.md)[Production Troubleshooting](https://jobicy.com/jobs?search_keywords=Production%20Troubleshooting.md) Sample interview questionsDescribe a production data-integration incident you investigated from initial alert through resolution.I would begin by confirming the scope, affected records, timestamps, and business impact. I would trace the data through source delivery, message parsing, transformation and mapping, storage, and downstream consumption, using logs, metrics, replayable test payloads, and database checks. After resolving the immediate issue, I would document the root cause, communicate status clearly to stakeholders, and add monitoring or automated tests to prevent recurrence. How would you validate an HL7v2 or FHIR integration before a clinical go-live? I would establish a test plan covering connectivity, authentication, message or resource structure, required fields, patient identity matching, code mappings, ordering, duplicate handling, error paths, and latency. I would validate representative and edge-case clinical data with both automated tests and joint client testing. Before go-live, I would define monitoring, escalation paths, rollback procedures, and reconciliation checks to ensure data arrives accurately in production. What approach would you take when a lab result is missing from the platform but the client expects an answer quickly? I would first identify the patient, result, source system, and expected arrival time, then determine whether the source emitted the relevant message. From there, I would trace the message through transport, parsing, mapping, validation, ingestion, and downstream processing to isolate the break. I would provide concise, evidence-based updates on current status, impact, owner, and next action while working toward restoration or a safe workaround. How do you design automated integration tests for external data pipelines? I use realistic, version-controlled fixtures and contract tests to validate schemas, transformations, mappings, idempotency, and error handling. Where possible, I run tests against isolated environments or service emulators and include end-to-end checks for critical workflows. I also include regression tests for previously observed production defects and make test results visible in the deployment pipeline. How would you use LLMs or automation to improve integration velocity without compromising clinical-data reliability? I would use automation for bounded tasks such as generating mapping drafts, summarizing interface documentation, identifying schema differences, and accelerating test-case creation. Any generated output would be reviewed through deterministic validation, domain rules, test suites, and human approval before production use. For clinical integrations, reliability, auditability, privacy, and clear fallback procedures would take priority over automation speed. ### Software Engineer, Data Integration In Brief * We’re a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives. * Join us in transforming healthcare from reactive to proactive. You’ll spearhead the engineering effort to build the bridge between massive, complex Electronic Health Record (EHR) systems and the Bayesian platform, delivering critical, real-time insights to help clinicians save lives. ### Who We Are Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data. We’re funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year. [Read more about our recent publication in Nature Medicine that associates our products with lives saved.](https://www.bayesianhealth.com/sepsis-research/?__hstc=251652889.1e7598f5de0ed9b513da684474e8a044.1710861879595.1710945070565.1710971833587.3&__hssc=251652889.1.1710971833587&__hsfp=1890770568) ### What you’ll do You will be at the forefront of a high-impact engineering mission, building the bridge between massive, complex Electronic Health Record (EHR) systems and the Bayesian platform to generate real-time lifesaving clinical insights that clinicians rely on. Working directly with our health system clients’ technical teams, you’ll turn fragmented data into immediate, actionable clinical insights that empower care teams to make the best decisions for their patients. Each integration is a partnership. An Implementation Lead owns the client relationship and project management; a Clinical Integration owns clinical workflow design and training. You own the technical workstream — which means you’re the engineer in the room. When a lab result isn’t reaching the Bayesian platform for a patient, you have thirty minutes and the client’s full attention to trace it from the inbound HL7 message through parsing, mapping, and ingestion, and tell them what happened. Responsibilities * Data Integration & Ingestion: Partner with the client’s technical teams to design and implement the data integration interface and ingestion pipelines that feed the Bayesian platform with real-time clinical data, powering insights that improve patient outcomes. * Integration Testing & Troubleshooting: Implement automated integration tests at the data layer, and work directly with client technical teams during integration testing to investigate and resolve issues, ensuring smooth and timely integrations. * Production Deployment & Go-Live: Execute the deployment process in close collaboration with the client’s technical team, ensuring build and configuration for the data interface, ingestion, and mapping are successfully promoted to production for a seamless launch. During go-live week, you will serve as the technical point of contact for any data integration issues, both internally and with the client’s teams, providing clear status updates to cross-functional partners so they can effectively manage client communication. * Integration Tooling & Automation: Develop frameworks and tooling, leveraging LLMs and automation, to increase the efficiency and velocity of our platform integrations as we scale. * Cross-Functional Collaboration: Work alongside an Implementation Lead, Clinical Integration, and the client’s technical teams to align the data integration workstream with the overall integration effort. ### Minimum qualifications * BS in Computer Science or equivalent practical experience * 3+ years building and deploying data pipelines to production, including integration with external APIs (Python preferred) * Strong ability to investigate and resolve data correctness problem end-to-end, across services, storage, and external data sources. * Experience with cloud solutions (AWS, Azure, etc.) and relational databases (PostgreSQL, MySQL, etc.) in a production environment * Experience writing automated integration tests for production systems * Strong communicator with a demonstrated ability to collaborate across functions, working effectively with internal stakeholders, including Project/Product Managers, to align on priorities and deliver results. ### Preferred qualifications * Experience with health data, integration with Electronic Health Records (EHR) systems, and Health IT interoperability standards such as HL7v2 and FHIR. * Experience rolling out production deployments, supporting systems through go-live via an on-call or support rotation, and triaging production issues * Experience working with enterprise customers, and the agility and responsiveness they require. * Experience building internal tooling or automation, including leveraging LLMs, to improve engineering velocity Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training. Show more [Apply now >](https://jobicy.com/jobs/152819-software-engineer-data-integration.md) > Annual salary information is not provided for this position. 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