We are looking for a Senior GCP Healthcare Data / AI Engineer to design and build a cloud-native healthcare data platform on Google Cloud Platform. The platform will process healthcare files from GCS, orchestrate pipelines using Pub/Sub/Eventarc, run processing workloads on Cloud Run/Dataflow, load structured and semi-structured data into Google Cloud Healthcare API FHIR Store, BigQuery, relational databases, and document databases, and provide a dashboard for end-to-end monitoring and traceability.

The role also includes building search and AI-assisted capabilities for healthcare PDFs, CCDA files, FHIR data, and other clinical documents using search indexes, embeddings, NER, semantic search, and optional LLM APIs.

Required Skills:

- 7+ years of hands-on database experience, data engineering experience including relational databases, Bigquery and document databases

- 5+ years of cloud experience, preferably on Google Cloud Platform.

- Strong experience with RDBMS technologies, including PostgreSQL, MySQL, SQL Server, Oracle, or equivalent relational database platforms.

- Strong experience designing and implementing data pipelines, including batch, streaming, event-driven, and API-based processing patterns.

- Strong programming experience, especially with Python, including object-oriented programming, modular application design, error handling, logging, unit testing, package management, and production-grade backend development.

- Experience with Dataflow, Apache Beam, or equivalent data pipeline frameworks.

- Experience integrating with external APIs, including authentication, retries, rate limits, error handling, and monitoring.

- Docker and CI/CD experience.

- Production monitoring, logging, alerting, and troubleshooting experience.

- Experience with search systems such as ElasticSearch, OpenSearch, vector databases, or hybrid keyword/vector search systems.

- Strong system design and architecture skills.

- Ability to mentor mid-level and junior engineers.

- Ability to create clear technical documentation, architecture diagrams, and implementation plans.

Preferred Skills:

- Database or cloud certification preferred

- Google Cloud Healthcare API experience.

- FHIR R4 experience, HL7, CCDA, clinical data integration, or healthcare interoperability experience.

- Gemini, Vertex AI, OpenAI API, or other LLM API integration experience.

- Terraform or Infrastructure-as-Code experience.

- HIPAA, PHI, healthcare security, or compliance experience.

- Experience building operational dashboards for cloud pipelines, data quality, or healthcare workflows.

Key Responsibilities:

- Design, build and support scalable healthcare data pipelines on GCP.

- Process healthcare files from GCS and route them through Pub/Sub, Eventarc, Cloud Run, Dataflow, BigQuery, FHIR Store, and downstream systems.

- Design relational and cloud database schemas for operational, analytical, and document-oriented workloads.

- Build APIs to monitor pipeline status, file processing, Pub/Sub messages, Dataflow jobs, Cloud Run services, BigQuery loads, and FHIR data validation.

- Design database models for pipeline metadata, orchestration configuration, processing history, audit logs, document metadata, and search indexes.

- Implement batch and streaming data pipelines.

- Build data validation, reconciliation, retry, and dead-letter handling processes.

- Integrate structured, semi-structured, and unstructured healthcare data.

- Support semantic search, NER, embeddings, and search result snippets for healthcare documents.

- Optimize database performance, query cost, indexing strategy, and storage design.

- Implement monitoring, logging, alerting, and operational traceability.

- Ensure secure handling of healthcare data, including PHI-aware design and least-privilege access.

- Mentor mid-level and junior engineers and define engineering best practices.