We're helping a US digital-health platform make patients' medical data accessible, consistent, and trustworthy. The platform brings together data from many clinical and administrative sources: lab results, diagnoses, medications, visits, claims and more. It standardizes this data into FHIR and exposes it through secure, standards-based APIs used by internal products and external partners.

The engineering scope covers healthcare data pipelines, interoperability services, and the core FHIR platform. It is built on Python and/or Node.Js/TypeScript, event-driven architecture (Kafka), cloud-native infrastructure, and AI-assisted engineering practices.

Requirements: 8+ years of professional software engineering experience (backend, data, or platform engineering), including 2+ years in a Tech Lead / Engineering Lead role

Proven experience in the Healthcare / HealthTech / Digital Health domain

Hands-on experience building systems that handle PHI under HIPAA requirements, including PHI-safe engineering practices, access control, and audit logging

Hands-on experience with FHIR R4 and healthcare interoperability standards (US Core, USCDI, HL7) Strong hands-on expertise in Python and/or Node.Js/TypeScript in production environments

Experience designing and operating distributed, high-scale systems: APIs, data pipelines, event-driven architecture (Kafka or equivalent) Strong understanding of system reliability: idempotency, error handling, retries, data quality, and observability

Experience with API security: OAuth 2.0 / OIDC, JWT

Solid SQL and NoSQL skills, data modeling, and schema evolution

Experience with cloud-native environments (AWS / Azure), Docker, Kubernetes, CI/CD, and automated testing





Proven ability to set technical direction and drive architecture decisions across components and teams

Experience leading and mentoring engineers through design reviews, code reviews, pairing, and knowledge sharing

Practical experience using AI coding agents (Claude Code or similar) as part of the development lifecycle, and sound judgment on when AI fits and when deterministic solutions are safer, especially where PHI is involved

Professional English (B2+) for direct collaboration with US-based technical and business stakeholders

Experience with data orchestration tools such as Prefect or Airflow.

Hands-on experience with Databriks

Responsibilities:

Experience building or operating a FHIR server (R4/R4B), Bulk FHIR, SMART on FHIR, Patient Access APIs

Knowledge of HL7 v2, C-CDA, and C-CDA-to-FHIR transformation

Familiarity with healthcare terminologies: SNOMED CT, LOINC, RxNorm, ICD-10, CPT

Experience with Databricks / Spark / Delta Lake or other lakehouse platforms

Experience with Master Patient Index (MPI), patient matching, or record linkage

Experience with payer data exchange (CARIN Blue Button, Da Vinci) or integrating EHR/EMR, HIE, pharmacy, or lab systems

Knowledge of US healthcare regulations: 21st Century Cures Act, ONC certification, CMS Interoperability Rule

Experience with consent management, resource-level access control, and tenant isolation

Experience building LLM-based capabilities for clinical data processing or data quality

Contributions to open-source healthcare or FHIR/HL7 communities

Contributions to the design and scaling of event-driven and real-time data pipelines using tools like Kafka, Spark, and DuckDB.

📌 Engeneering Lead With Healthcare Experience (Madrid)
🏢 Intellias
📍 Madrid