Ivan Ermilov
Lead Engineer at Deutsche Bank
Leipzig, Saxony, Germany
Summary
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Rockstar🎓
Top SchoolIvan Ermilov is a Lead Engineer based in Leipzig with 14 years of experience building and operating distributed systems and cloud-native infrastructure. He blends hands-on DevOps expertise—demonstrated by Dockerized HBase, Hadoop and Spark workbench contributions—with leadership roles across finance and industrial tech, most recently at Deutsche Bank. His background includes a PhD in Computer Science, giving him a research-driven approach to complex system design and reliability. Known for scripting robust container entrypoints and orchestration logic, he focuses on making heavyweight big-data stacks runnable and repeatable in development and production. Colleagues rely on him to translate deep technical problems into maintainable deployment patterns and automated build processes.
14 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Leipzig UniversityDiploma Engineer, Computer and Information Systems Security/Information Assurance, Diploma Engineer, Computer and Information Systems Security/Information Assurance at Saint Petersburg University of Telecommunications
English, Russian, German
Github Skills (15)
sh10
hbase10
bash10
script10
docker10
spark10
shell10
hadoop10
devops10
containerization10
dockers10
scripting10
build-automation10
github-ci8
githubaction-workflow8
Programming languages (23)
Github contributions (5)
big-data-europe/docker-hbase
Jul 2017 - Apr 2018
Role in this project:
DevOps Engineer
DevOps EngineerContributions:17 commits, 21 pushes, 2 branches in 9 months
Contributions summary:Ivan focused on configuring and setting up the environment for running Apache HBase in a Dockerized environment. Their contributions involve modifying the `entrypoint.sh` scripts to configure HBase properties, and writing scripts to start HBase master and regionservers. Further, the user implemented logic for preconditions in containers using `wait_for_it`. The changes indicate work towards creating a runnable local and/or distributed HBase cluster using Docker.
big-data-europe/docker-hadoop-spark-workbench
Mar 2016 - Oct 2018
[EXPERIMENTAL] This repo includes deployment instructions for running HDFS/Spark inside docker containers. Also includes spark-notebook and HDFS FileBrowser.
Role in this project:DevOps Engineer
DevOps EngineerContributions:42 commits, 10 PRs, 37 pushes in 2 years 6 months
Contributions summary:Ivan primarily contributed to the infrastructure and build process of the project. They wrote shell scripts to configure Hadoop and Spark components within Docker containers, modified build scripts, and updated image building processes. Key contributions include creating Dockerfiles, modifying entrypoint scripts, and adapting the build process to integrate Hue. They also refactored the build process to align with a new organizational structure.
containersbigdatadeploymentinstructionsnotebook
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