Healthcare Data Handling & Notification Platform
Budget: ₹37,500 – ₹75,000 INR
Project Title
Healthcare Data Ingestion & Notification Platform (HL7, EMR, CI/CD, Kafka, AWS, Java/Spring Boot)
Project Description
We are developing a healthcare-genomics data platform focused on ingesting EMR and lab data (including HL7 feeds), transforming the data, and triggering secure, scalable notification systems with attachments. We are seeking a highly experienced backend engineer or architect who can help design, implement, and optimize the solution while ensuring compliance with HIPAA and CLIA regulations.
Scope of Work
1. Ingestion Pipeline (EMR / Lab / HL7)
Design and implement ingestion pipelines for HL7, FHIR, flat files, and lab feeds
Build or integrate HL7 transformers (either custom or using libraries)
Support both input and output processing logic
Interface with EHR/EMR systems and external lab sources
2. Backend Architecture
Modularize existing microservice architecture
Apply Domain-Driven Design (DDD), schema registries, and shared libraries
Provide guidance on container orchestration with ECS, EKS, or serverless (Fargate, Lambda)
3. Data Security and Compliance
Implement HIPAA and CLIA-compliant data handling across all stages
Secure transmission and storage of email content and attachments
Use encryption and secure temporary storage mechanisms (e.g., S3 with pre-signed URLs)
4. AWS Cloud Services
Design and optimize ingestion and transformation using:
AWS Glue, S3, Lambda, EMR, Step Functions, SNS/SQS, EventBridge
Architect scalable and cost-efficient long-term storage and retrieval
5. Notification System
Build or optimize a scalable email notification system
Handle attachments, retries, delivery logging, and failure tracking
Implement background jobs for delivery and email batching
Ensure distributed job handling using ECS Fargate or other distributed schedulers
6. CI/CD and DevOps
Set up or improve CI/CD pipelines (Jenkins, GitHub Actions, Argo, etc.)
Integrate automated quality gates (SonarQube, Fortify, integration tests)
Use versioned deployments and blue-green or canary rollout strategies
7. Java and Spring Boot
Implement background scheduling and distributed locking in Spring Boot
Use Java 11 or 17 best practices and justify version decisions
Simplify management of multiple frameworks and improve modularity
Preferred Tech Stack
Languages: Java 11+/Spring Boot, Python
Cloud: AWS (Lambda, S3, Glue, EMR, ECS/EKS, Fargate)
Data: HL7, FHIR, PostgreSQL, JSON, Parquet
Messaging: Kafka, SQS, SNS
CI/CD: Jenkins, GitHub Actions, SonarQube
Monitoring: CloudWatch, Prometheus, ELK or Grafana
Deliverables
HL7 ingestion and transformation pipeline
Secure notification system with background job handling
CI/CD pipelines with quality gates and rollback support
Documentation and diagrams (architecture, deployment, compliance checklist)
Codebase with test coverage and deployment scripts
Required Experience
Hands-on experience with healthcare data formats (HL7, FHIR, lab systems)
Strong AWS experience (EMR, Glue, S3, Lambda, EventBridge)
Built distributed, secure backend services (Java, Spring Boot, Kafka)
Familiarity with compliance constraints like HIPAA and CLIA
Experience handling background jobs, distributed scheduling, and email delivery systems
Healthcare Data Ingestion & Notification Platform (HL7, EMR, CI/CD, Kafka, AWS, Java/Spring Boot)
Project Description
We are developing a healthcare-genomics data platform focused on ingesting EMR and lab data (including HL7 feeds), transforming the data, and triggering secure, scalable notification systems with attachments. We are seeking a highly experienced backend engineer or architect who can help design, implement, and optimize the solution while ensuring compliance with HIPAA and CLIA regulations.
Scope of Work
1. Ingestion Pipeline (EMR / Lab / HL7)
Design and implement ingestion pipelines for HL7, FHIR, flat files, and lab feeds
Build or integrate HL7 transformers (either custom or using libraries)
Support both input and output processing logic
Interface with EHR/EMR systems and external lab sources
2. Backend Architecture
Modularize existing microservice architecture
Apply Domain-Driven Design (DDD), schema registries, and shared libraries
Provide guidance on container orchestration with ECS, EKS, or serverless (Fargate, Lambda)
3. Data Security and Compliance
Implement HIPAA and CLIA-compliant data handling across all stages
Secure transmission and storage of email content and attachments
Use encryption and secure temporary storage mechanisms (e.g., S3 with pre-signed URLs)
4. AWS Cloud Services
Design and optimize ingestion and transformation using:
AWS Glue, S3, Lambda, EMR, Step Functions, SNS/SQS, EventBridge
Architect scalable and cost-efficient long-term storage and retrieval
5. Notification System
Build or optimize a scalable email notification system
Handle attachments, retries, delivery logging, and failure tracking
Implement background jobs for delivery and email batching
Ensure distributed job handling using ECS Fargate or other distributed schedulers
6. CI/CD and DevOps
Set up or improve CI/CD pipelines (Jenkins, GitHub Actions, Argo, etc.)
Integrate automated quality gates (SonarQube, Fortify, integration tests)
Use versioned deployments and blue-green or canary rollout strategies
7. Java and Spring Boot
Implement background scheduling and distributed locking in Spring Boot
Use Java 11 or 17 best practices and justify version decisions
Simplify management of multiple frameworks and improve modularity
Preferred Tech Stack
Languages: Java 11+/Spring Boot, Python
Cloud: AWS (Lambda, S3, Glue, EMR, ECS/EKS, Fargate)
Data: HL7, FHIR, PostgreSQL, JSON, Parquet
Messaging: Kafka, SQS, SNS
CI/CD: Jenkins, GitHub Actions, SonarQube
Monitoring: CloudWatch, Prometheus, ELK or Grafana
Deliverables
HL7 ingestion and transformation pipeline
Secure notification system with background job handling
CI/CD pipelines with quality gates and rollback support
Documentation and diagrams (architecture, deployment, compliance checklist)
Codebase with test coverage and deployment scripts
Required Experience
Hands-on experience with healthcare data formats (HL7, FHIR, lab systems)
Strong AWS experience (EMR, Glue, S3, Lambda, EventBridge)
Built distributed, secure backend services (Java, Spring Boot, Kafka)
Familiarity with compliance constraints like HIPAA and CLIA
Experience handling background jobs, distributed scheduling, and email delivery systems