# Konstantine Karantasis

> Staff Software Engineer at Confluent, Apache Kafka Committer and PMC Member

Location: San Francisco, California, United States
Profile: https://flows.cv/konstantinekarantasis

I like writing software that is fast and scalable, pleasant to read, and useful. 
With a strong background in high performance computing, I have an everlasting fascination with the applications of parallelism in computer systems. 

For the past few years I have been focusing on building scalable distributed systems that process big amounts of data modeled as events in real-time and run on premise and in the cloud. 

My interests and expertise in keywords:
* Scalable event streaming and distributed systems.
* Cloud computing and orchestration.
* Parallel computing and supercomputing.

## Work Experience
### Staff Software Engineer II @ Confluent
Jan 2025 – Present | San Francisco Bay Area

### Staff Software Engineer @ Confluent
Jan 2021 – Jan 2025
Member of the Kafka Connect team, I am working on seamless and scalable integration of data systems with Apache Kafka in the cloud and on-premise.

### Senior Software Engineer @ Confluent
Jan 2016 – Jan 2020 | San Francisco Bay Area

### Apache Kafka PMC member @ The Apache Software Foundation
Jan 2021 – Present

### Apache Kafka Committer @ The Apache Software Foundation
Jan 2020 – Present

### Senior Software Engineer @ Big Data Startup in Stealth-mode
Jan 2016 – Jan 2016
Led the efforts to accelerate big data workloads on Apache Spark and Apache Kafka using native code and specialized hardware accelerators.

### Tech Yahoo, Software Engineer @ Yahoo
Jan 2014 – Jan 2016
I worked on enabling and optimizing big data analytics for Yahoo's massive audience data on a technology stack that included Druid, Kafka, Hadoop and Spark. Designed and implemented key parts of low latency web-services for ad-hoc real-time queries on streamable and aggregatable data, such as topN, time-series and group-by queries.

Led the performance evaluation and contributed to capacity planning of Yahoo’s next generation data analytics clusters for audience data.

Tech stack: Kafka, Druid, Hadoop, Spark, Java 8, ReactiveX, Scala, Groovy

### Postdoctoral Research Associate, Computer Science @ University of Illinois at Urbana-Champaign
Jan 2011 – Jan 2014
I designed and implemented with Andrew Lenharth and Donald Nguyen the first parallel versions of the most widely used algorithms for bandwidth and wavefront reduction in sparse matrices and social networks. These algorithms have significant applications ranging from numerical computing to data visualization. 

You may find these high performance versions of Cuthill-McKee and Sloan algorithms along with many other fascinating parallel graph algorithms in the latest version of Galois.

Tech stack: Galois, Boost, C++11, R, Stream-based lazy evaluation computing.

### Visiting Lecturer, Electrical and Computer Engineering @ University of Illinois at Urbana-Champaign
Jan 2011 – Jan 2013


## Education
### Ph.D. in Computer Science and Engineering
University of Patras

### M.Sc. in Computer Science and Engineering
University of Patras

### Bachelor of Science (B.Sc.) (5-year degree) in Computer Engineering and Informatics
University of Patras


## Contact & Social
- LinkedIn: https://linkedin.com/in/karantasis
- Portfolio: http://web.engr.illinois.edu/~kik/

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Source: https://flows.cv/konstantinekarantasis
JSON Resume: https://flows.cv/konstantinekarantasis/resume.json
Last updated: 2026-04-12