Gábor is available for hire

Gábor Attila Kiss

Verified Expert in Engineering

Data Engineer and Developer

Location

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.

Software Engineering Distributed Systems Data Engineering Java Microservices ETL Scala Big Data Machine Learning Python Docker Apache Kafka Apache Spark Kafka Streams Kotlin

Portfolio

IncQuery Group

Kotlin, Kubernetes, Amazon Web Services (AWS), Elasticsearch, Knowledge Graphs...

Ericsson

Kubernetes, Java, Apache Spark, Apache Kafka, Scala, Kafka Streams

Ericsson

Python, Java

Experience

Java - 6 years Python - 6 years Distributed Systems - 6 years Microservices - 6 years Kubernetes - 4 years Data Engineering - 3 years Scala - 2 years Apache Spark - 2 years

Availability

Part-time

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

Ericsson

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

Ericsson

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

Intern

2014 - 2015

Quanopt

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

Experience

Ericsson Expert Analytics

https://www.ericsson.com/en/digital-services/network-automation/telecom-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.

Skills

Languages

Java, Scala, Python, Kotlin

Paradigms

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

Other

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

Frameworks

Apache Spark, Hadoop, Vert.x

Tools

Kafka Streams, IntelliJ IDEA, Helm, BigQuery

Platforms

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

Libraries/APIs

Pandas, Scikit-learn, Matplotlib, NumPy

Storage

Elasticsearch

Education

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

Certifications

JUNE 2020 - PRESENT

Applied Data Science Camp

Ericsson

FEBRUARY 2020 - PRESENT

Docker + Kubernetes Administration with Helm (KBS-105)

Component Soft

Collaboration That Works

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