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.
- Robust 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.

Work from home, Timings (2.00 P.M - 11.00 P.M ISD)

If you are interested, please fill the below forms:

https://forms.office.com/r/ByhxcrTx7n

📌 Senior Healthcare Data / AI Engineer (Tamil Nadu)
🏢 S2m Health Care
📍 Tamil Nadu