Karthik Janaki
Data Engineering & Architecture Lead (VP) | Scalable Data Platforms, Lakehouse & Streaming | Databricks, AWS, Spark
- Role
- VP, Data Engineering Manager & Principal Data Architect (Senior Manager of Engineering) at JPMorganChase
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Karthik Janaki
Engineering manager leading a team of data engineers to design and build scalable data platforms, lakehouse and streaming solutions on Databricks and AWS.Owns end‑to‑end data architecture, technical direction, and delivery while coaching and growing a high‑performing engineering team.
Experience
VP, Data Engineering Manager & Principal Data Architect (Senior Manager of Engineering)
Sep 2022 — Present · Jersey City, NJ, US
Leading and managing engineering teams focused on delivering a robust cloud data warehouse-as-a-service application, catering to diverse analytical use cases- Led the design and implementation of robust data pipelines for batch and streaming applications using an optimized stack of Databricks and AWS services.Spearheading the design and implementation of data integration solutions that act as efficient data ingestion gateways to the warehouse- Establishing and leading feature engineering teams, providing expert guidance in application development, architecture, and lifecycle management- Collaborating with technical leads and stakeholders to design seamless integration solutions for the data warehouse- Demonstrating hands-on expertise in AWS services, a wide range of data engineering technologies, Spring Boot, and security applications- Proficient in developing applications using microservice architecture and adept at leading engineering teams involved in UI, data services, and back-end development.
Education
University of Cincinnati Carl H. Lindner College of Business
Master of Science (M.S.), Information Systems
2014 — 2015
Vellore Institute of Technology
Bachelor of Technology (BTech), Computer Science
2007 — 2011
Skills
- Sql
- Restful Webservices
- Hibernate
- Apache Kafka
- Spring Framework
- Hbase
- Java
- Hadoop
- Hive
- Oracle Database
- Apache Spark
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