LEAD GCP Data Engineer- PAN INDIA

Role & responsibilities

We are looking for a LEAD GCP Data Engineer to help design, develop, test, and support cloud-based healthcare data pipelines and backend services on Google Cloud Platform. This role will work closely with senior engineers to process healthcare files from GCS, support event-driven workflows using Pub/Sub/Eventarc, implement data processing using Cloud Run/Dataflow, load data into BigQuery, relational databases, document databases, and support integration with FHIR Store and downstream applications.

The role may also support search and AI-assisted capabilities for healthcare PDFs, CCDA files, FHIR data, and clinical documents using search indexes, embeddings, NER tools, and semantic search pipelines.

Client inputs:

We need one Lead GCP Data Engineer with 10+ years experience. He should be able to handle the team and guide them. AI Experience preferred.

Required Skills

• 5+ years of hands-on database experience, data engineering experience including relational databases, Bigquery and document databases
• 5+ years of hands-on database experience, including SQL, relational database concepts, data modeling, query writing, indexing basics, and data validation.
• 5+ years of cloud experience, preferably on Google Cloud Platform.
• Strong programming experience, especially with Python, including:
• Object-oriented programming
• Modular code development
• Error handling
• Logging
• Unit testing
• Package management
• Backend or data pipeline development
• Experience with RDBMS technologies, such as PostgreSQL, MySQL, SQL Server, Oracle, or equivalent.
• Experience building or supporting data pipelines, including batch, event-driven, API-based, or streaming workflows.
• Hands-on experience with GCP services such as: GCS, Pub/sub, Cloud Run, Data flow
• Experience integrating with external APIs, including authentication, retries, error handling, and basic monitoring.
• Docker experience for containerized application development.
• Git/GitHub experience, including branching, pull requests, and code reviews.
• Experience with CI/CD pipelines, preferably using GitHub Actions, Cloud Build, or similar tools.
• Ability to debug application, pipeline, database, and cloud service issues using logs and monitoring tools.
• Ability to write clean, maintainable, testable, and well-documented code.
• Ability to work from architecture diagrams, technical specifications, and implementation tickets.

Preferred Skills

• Cloud certification or Database Certification
• Google Cloud Healthcare API experience.
• Exposure to FHIR R4, HL7, CCDA, clinical data integration, or healthcare interoperability.
• Exposure to embeddings, semantic search, ElasticSearch, OpenSearch, or vector databases.
• Experience with Gemini, Vertex AI, OpenAI API, or other LLM API integrations.
• Terraform or Infrastructure-as-Code exposure.
• HIPAA, PHI, healthcare security, or compliance awareness.

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.
• Debug production and non-production issues using Cloud Logging, Cloud Monitoring, and application logs.
• Participate in code reviews and follow engineering best practices.
• Work with senior engineers to implement scalable, secure, and maintainable cloud data solutions.

Preferred candidate profile

Perks and benefits