Gábor Attila Kiss, Developer in Budapest, Hungary
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Gábor Attila Kiss

Verified Expert  in Engineering

Data Engineer and Developer

Budapest, Hungary
Toptal Member Since
October 26, 2020

Gábor is a software and data engineer, specializing in big data, stream processing, and machine learning. He builds elegant solutions for discovering actionable insights in real time, leveraging highly scalable microservice architecture—even on top of petabyte-scale data. Gábor has been a developer at Ericsson since completing his master's degree in computer science engineering in 2017. He looks forward to leveraging his expertise to deliver large-scale data engineering solutions in new places.


IncQuery Group
Kotlin, Kubernetes, Amazon Web Services (AWS), Elasticsearch, Knowledge Graphs...
Kubernetes, Java, Apache Spark, Apache Kafka, Scala, Kafka Streams
Python, Java




Preferred Environment

Kubernetes, Visual Studio Code (VS Code), IntelliJ IDEA

The most amazing...

...project I've built is a machine learning solution for detecting anomalies in one of the largest network operator's system in the United States.

Work Experience

Senior Software Engineer

2021 - PRESENT
IncQuery Group
  • Drove the transition of IncQuery Suite into a cloud-native solution by leveraging Kubernetes capabilities and reducing memory footprint significantly.
  • Implemented modern techniques for data storage, handling, and transportation.
  • Implemented a cluster-wide monitoring solution using Elastic Stack with autoconfiguration for dynamic deployments.
Technologies: Kotlin, Kubernetes, Amazon Web Services (AWS), Elasticsearch, Knowledge Graphs, Vert.x, Microservices, Distributed Systems, ETL

Experienced Developer

2018 - 2021
  • Built a highly scalable solution that uses machine learning to find a misbehaving group of network components in billions of combinations in different slices of the network.
  • Developed a real-time solution to calculate an accurate, accumulated count of subscribers impacted by a network error.
  • Specified the requirements for the aforementioned solution—from data collection to UI—covering five different stages and teams. Designed and documented the architectural specification and supported the integration from the technical point of view.
Technologies: Kubernetes, Java, Apache Spark, Apache Kafka, Scala, Kafka Streams

Experienced Developer

2017 - 2018
  • Built an easily overseeable lifecycle management solution for virtualized network functions in BPMN.
  • Oversaw customer deployment and directed customization on site.
  • Developed a highly customizable Python framework for Ericsson's IP Multimedia solutions product palette with support for network function-specific customization.
Technologies: Python, Java


2014 - 2015
  • Developed and delivered a hands-on workshop on OpenStack administration.
  • Built a monitoring solution for a system on a dynamically scaling infrastructure and for the infrastructure itself.
  • Developed a design proposition for a customer's application performance monitoring solution.
Technologies: Application Performance Monitoring, Monitoring, OpenStack

Ericsson Expert Analytics

Ericsson Expert Analytics (EEA) is a network monitoring and analytics solution. It collects data from all across the network operator's system. I was tasked with delivering EEA's first machine learning solution, an anomaly detection system working on the vast amount of collected data. My role was to prototype, design, document, drive cooperation, and participate in the development of the final solution.

Analytical Dashboards and Forecasts for a Real-Estate Management Company

The company's analytical dashboards provided by their enterprise management solution limited their growth. They needed tailor-made dashboards and predictions to support their business processes; marketing, expansion, and market research.
2015 - 2017

Master's Degree in Computer Science Engineering

Budapest University of Technology and Economics - Budapest, Hungary

2010 - 2014

Bachelor's Degree in Computer Science Engineering

Budapest University of Technology and Economics - Budapest, Hungary


Applied Data Science Camp



Docker + Kubernetes Administration with Helm (KBS-105)

Component Soft


Pandas, Scikit-learn, Matplotlib, NumPy


Kafka Streams, IntelliJ IDEA, Helm, BigQuery


Microservices, ETL, Parallel Computing, Data Science, Distributed Computing


Apache Spark, Hadoop, Vert.x


Java, Scala, Python, Kotlin




Apache Kafka, Docker, Visual Studio Code (VS Code), Kubernetes, Amazon Web Services (AWS), Google Cloud Platform (GCP)


Software Engineering, Data Engineering, Distributed Systems, Machine Learning, Big Data, Cloud Computing, Knowledge Graphs

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