Lead AI Data Engineer - Healthcare Payer Systems, Claims & Payment Integrity

****Must-Have: A minimum of 5 years of experince with Healthcare Payer Systems, Claims & Payment Integrity****

Primary Skills:

• ETL Fundamentals, SQL, SQL (Basic + Advanced), Alation, Talend, Matillion, Python, Data Warehousing, IICS, Modern Data Platform Fundamentals, Data Modelling Fundamentals, PLSQL, T-SQL, Stored Procedures

Specialization

• ETL Specialization: Lead Data Engineer

Job Title: Lead Data Engineer (AWS-based solutions, Kafka integrations, and data pipelines), Python + Java, Payment integrity
Experience Level: 8+ Years (3+ Years in Technical Leadership)
 
Role Overview
We are seeking a highly skilled Lead Engineer to lead the architecture, design, and development of the project, a configuration-driven, event-based data and rule-processing ecosystem supporting healthcare payer workflows.
 
This role requires strong expertise in building metadata-driven systems, rule engines, and configurable integration frameworks within a cloud-native architecture. The ideal candidate will also possess solid knowledge of healthcare systems, particularly Payment Integrity and claims processing workflows, and be capable of designing systems that support fraud detection, pre-pay/post-pay validation, and rule-based adjudication enhancements.

Key Responsibilities:
Technical Leadership:

• Lead end-to-end engineering for the PISCES HUB initiative.
• Provide architectural direction and hands-on leadership.
• Mentor development teams and enforce engineering best practices.
• Ensure scalability, configurability, and maintainability of rule-driven systems.
• Collaborate with Product, Payment Integrity SMEs, and Enterprise Architecture teams.
• Strong knowledge on Dynatrace
• Knowledge on Windsurf to accelerate development.
• Design and build:

• Metadata-driven pipelines and workflow orchestration engines.
• Dynamic business rule engines for payment integrity use cases.
• Configurable API/data integration frameworks.
• Template-based or parameterized services.

• Develop JSON/YAML/XML-based configuration interpreters.
• Enable runtime rule updates without redeployment.
• Design version-controlled rule lifecycle frameworks with auditability.
• Design data models for:

• Rule storage and versioning
• Claims validation configurations
• Payment integrity audit trails

• Optimize SQL/NoSQL databases for high-volume rule evaluation.
• Ensure rule governance, auditability, and compliance tracking.
• Strong understanding of:

• Healthcare payer systems
• Claims adjudication workflows
• Pre-pay and post-pay validation logic
• Payment Integrity rule frameworks
• Fraud, Waste & Abuse detection concepts

• Experience integrating with core healthcare systems (e.g., Facets, QNXT, Amisys or similar).
• Ability to translate payment integrity business requirements into scalable technical design.
• Design and implement event-driven systems using Kafka.
• Build microservices deployed in AWS environments:

• EKS, ECS, Lambda
• S3, RDS, DynamoDB

• Ensure high scalability and resilience for healthcare transaction workloads.
• Implement CI/CD pipelines with automated testing.
• Containerize services using Docker and Kubernetes.
• Apply GitOps workflows for deployment automation.
• Ensure observability, monitoring, and production readiness.
• 8+ years of software engineering experience.
• 3+ years leading engineering teams or owning platform architecture.
• Strong proficiency in:

• Python or Java (both preferred)

• Proven experience building configuration-driven systems.
• Strong database modeling expertise (SQL & NoSQL).
• Experience designing JSON/YAML/XML configuration interpreters.
• Hands-on experience with Kafka and event-driven architecture.
• Experience with AWS cloud services (EKS, ECS, Lambda, S3, RDS, DynamoDB).
• Strong grasp of CI/CD, Docker, Kubernetes, and GitOps.
• Strong knowledge of healthcare systems with focus on Payment Integrity.
• Exposure to Machinify platform or similar AI-driven payment integrity systems.
• Experience integrating rule engines with AI/ML-based fraud detection systems.
• Experience building healthcare data hubs or enterprise integration platforms.
• Familiarity with HIPAA-compliant system design.
• Strong system design and architectural thinking.
• Ability to translate healthcare business rules into scalable technical solutions.
• Ownership mindset with strong accountability.
• Strong cross-functional collaboration and communication skills.
• Ability to balance long-term platform vision with delivery timelines.