Lead developers in building a strategic target consent and preference management architecture. Stay current with industry privacy and consent technology trends to continuously improve compliance and performance. Develop privacy and consent management solutions supporting the holistic architecture.
Responsibilities:
Lead the development of strategic target consent and preference management architecture.
Develop scalable, hierarchical data models for consent management.
Implement event-driven architecture using a message broker for real-time data flow.
Ensure synchronization and reporting of Patient_ID changes from MDM to consumers.
Implement logging and observability using Splunk.
Develop front-end solutions using React and Node.js, and backend solutions with Java Spring.
Ensure data security and manage data at rest and archival processes.
Build domain-level solutions with robust database integration.
'Must Have' Experience:
Overall industry experience: 20+ years, minimum 5 years of experience in enterprise-level architecture
Ability to architecture a distributed highly performant and scalable system
Experience in product development rather than services.
6+ years of central platform development experience or any experience with consent and preference solution is preferred.
4+ years of solution architecture experience.
Exceptional communication skills for presenting and influencing various stakeholders including senior leadership
Proven relationship-building skills, facilitating win-win solutions and obtaining organizational support.
Innovative thinking beyond traditional boundaries.
Experience collaborating with diverse teams including offshore teams
Diverse and deep experience in microservices architecture, domain-driven design, and RESTful services, including GraphQL.
Experience with the following:
Large scale APIs, Apache Kafka.
Backend development with Java Spring.
Message brokers for event publication from Identity Management Systems.
Experience with scalable hierarchical data models, data migration, managing data at rest, and data archival processes.
Publishing and synchronizing Patient IDs from MDM to consumers.
Logging into Splunk for observability.
Dashboarding with Dynatrace.
Static code analysis using SonarQube.
Building domain-level solutions.
Database-level integration with other applications.