Shashi Kanth K

About Shashi Kanth K

Engineering Manager and Data Platform Leader with 15+ years in distributed systems and 7+ years scaling enterprise data platforms at Cardlytics, powering 200M+ financial transactions daily.Led the post-acquisition unification of Cardlytics and Bridg multi-business datasets, architecting a PII-free customer identity resolution framework that enabled cross-platform targeting, reduced duplicate rewards, and unlocked new monetization opportunities.I specialize in designing, developing distributed systems, micro services and operating cloud-native lakehouse architectures on AWS and Databricks, leveraging.Net, ASP.Net, Kafka, Spark, PySpark, SQL, EMR, Hudi, Airflow, and S3 to deliver high-throughput, governed, production-grade systems.My focus is building trusted, governed platforms that power business intelligence, machine learning, advertiser targeting, and AI-driven automation, while coaching high-performing engineering teams to deliver with ownership and operational excellence.I’m most energized by complex technical challenges in distributed data systems, platform scalability, and production data architecture.

Experience

1. Engineering Manager - Core Data Platform

   Cardlytics

   Sep 2022 — Present · Atlanta, GA, US

   Lead architecture and evolution of Cardlytics’ Core Data Platform powering 200M+ daily transactions across 2 in 3 U.S./U.K. card purchases, Played a pivotal role in unifying Cardlytics and Bridg data ecosystems following acquisition, enabling new line of business, BI, ML, and advertiser reporting at scale.• Modernized legacy systems into a cloud-native lakehouse (Spark, EMR, Hudi, S3, Airflow, Athena) delivering high-throughput, low-latency distributed processing• Engineered distributed Spark ingestion pipelines for Financial Institution data, reducing processing time 90%(36h → <4h) with 99.9%+ reliability• Designed a multi-tenant data mesh framework with schema validation, reprocessing, retention policies, and observability• Optimized EMR and Spark workloads, reducing infrastructure and data scan costs by 60%• Led post-acquisition unification of Cardlytics + Bridg datasets, building a PII-free entity resolution engine (Spark/SQL) using purchase patterns and demographic attributes to generate Unified Customer IDs across 100M+ records• Reduced duplicate rewards and unlocked new cross-business targeting capabilities• Re-architected the rewards engine into a template-driven, configuration-based platform, enabling Product to launch new reward models in hours without code changes• Implemented automated golden test suites and validation workflows to ensure deterministic reward evaluation and scalable rollouts• Reduced pipeline incidents by 80%, improved MTTR by 60%, and scaled platform adoption to 100+ internal consumers

Education

• Jawahar Navodaya Vidyalaya

  AISSCE

• Jawaharlal Nehru Technological University

  Bachelor of computer science engineering, Computer Science

  2007 — 2011