Kamaraj Dhanasekaran

Leading architectural initiatives for Freshmarketer (Campaigning Tool) and Freshsales (CRM) products serving
50, 000+ customers globally and handling millions oftransactions per day
Architected the Import Platform and External System Sync end-to-end, delivering 80% faster processing,
improved stability, and reduced infrastructure cost.
Led technical design reviews to ensure enterprise-grade access controls aligning product design with
security and compliance.
Re-architected Shopify integration by implementing event driven data pipelines (Kafka), enabling
processing of more than 1Million records in minutes and improving overall processing efficiency by 90%.
Drove CRM core modules end-to-end (API design, data modeling, workflow orchestration, business-critical
flows), enabling highly efficient APIs with end-customer response times under 400 ms.
Implemented secure service to service and API access using OAUTH 2.0, JWT with Spring Security.
Technologies: Java, Spring Boot, Spring cloud, Spring Security, Kafka, MySQL, Elasticsearch, Redis,
Memcached, REST, Helm

Led architecture design and technical decision-making for CRM SaaS products, including
Freshmarketer and Freshsales distributed microservices platforms, defining HLD/LLD,
scalability patterns, and reliability strategies. Mentored and guided a team of 10 engineers
on distributed system design, performance optimization, and production reliability.
• Architected and led development of cloud-native backend platforms for CRM -
Freshmarketer and Freshsales, supporting 50, 000+ global customers and
millions of daily transactions with high availability and low latency SLAs.
• Designed distributed data ingestion and synchronization platforms using parallel
processing and batching strategies, improving data throughput by 80% while
reducing infrastructure costs by ~30%.
• Re-architected Shopify integration using event-driven pipelines with Kafka, enabling
processing of 1M+ records in few hours and improving integration efficiency by
80% and enabling near-real-time data synchronization across SaaS platforms
• Implement asynchronous workflow of Contact management systems using Netflix
Conductor .
• Led development of high-performance CRM core modules and APIs with response
times under 400ms, improving platform scalability and secured API communication
using OAuth 2.0, JWT, and Spring Security.
• Managed AWS (Amazon Web Services) cloud infrastructure including EKS, RDS,
and S3, implementing autoscaling, observability, and zero-downtime deployment
strategies for highly available production systems.
• Technologies: Java, Spring Boot/Cloud/Security, Kafka, MySQL, Elasticsearch, Redis,
REST, Helm, Python (AI/automation), Netflix Conductor

• Led an 8-member team delivering a high-scale Policy Administration system for
Liverpool Victoria Insurance, managing 4M+ annual customers in Life and General
Insurance domains.
• Architected scalable Spring Boot microservices, integrating policy systems with
multiple external vendors using microservices patterns (Eureka, Zuul, Spring Cloud
Config, REST APIs).
• Designed an automated recovery framework for messaging failures, reducing
manual intervention by 80%, and increasing policy renewal success from 70% to
80%.
• Implemented event-driven distributed workflows for eight downstream systems,
ensuring reliable, asynchronous communication with resilience strategies (timeouts,
retries, circuit breakers).
• Technologies: Java, Spring Boot/Security, Python, RabbitMQ, Kafka, MySQL,
Elasticsearch, Redis, REST APIs

• Developed and enhanced insurance claims administration and CRM modules for a
leading Europe-based insurance provider, supporting 2M+ customers annually.
• Built claims administration solutions using Java/J2EE, Spring, Hibernate, and
delivered enterprise integrations via SOAP Web Services.
• Developed migration platforms using Kafka pipelines and scheduled workflows,
reliably migrating 2M+ claims and policies from mainframe to modern systems.
• Optimized workflow orchestration, reducing turnaround time from 2 minutes to
30 seconds, and cutting infrastructure costs by 15%.
• Technologies: Java, Spring, Hibernate, Kafka, Oracle, Elasticsearch