Gennady Shabanov verfügbar

Gennady Shabanov

Java Software Engineer

verfügbar
Profilbild von Gennady Shabanov Java Software Engineer aus Berlin
  • 10315 Berlin Freelancer in
  • Abschluss: M.S. Computer Science at Technical Munich University, 11.2014
  • Stunden-/Tagessatz: 65 €/Std. 520 €/Tag
  • Sprachkenntnisse: englisch (verhandlungssicher) | russisch (Muttersprache)
  • Letztes Update: 20.03.2020
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SKILLS
  • 7+ years of professional expertise in Information Technologies (IT) industry
  • Solid engineering, coding and problem-solving skills. Ability to write high-performance production quality code
  • Experience working with Java, Spring Boot, AWS, Hibernate, Jenkins, Kafka, ELK, Hadoop, Spark, MySQL, Postgres, Oracle, PL/SQL, SQL, Kubernetes, Airflow
  • Experience working with service-oriented architectures and REST-based API design
  • Experience in architecting highly scalable, distributed systems
  • Experience in building end-to-end large-scale machine learning systems
  • Experience in launching a startup from scratch
PROJEKTHISTORIE
  • 08/2019 - 11/2019

    • Simplaex GmbH
    • 10-50 Mitarbeiter
    • Internet und Informationstechnologie
  • Senior Software Engineer
  • Implementing infrastructure for processing big data in the advertisement field

    Tasks: Build infrastructure to process every day over 80TB with Spark and Kafka

    Implemented:

    • Created Kubernetes configuration files to migrate from AWS ECS to EKS

    • Significantly improved performance of a spring application consuming data from clients

    Tech stack: AWS, Amazon Elastic Kubernetes Service, Spark, Kafka, ELK, Airflow


  • 04/2015 - 07/2019

    • Visual Meta GmbH
    • 50-250 Mitarbeiter
    • Internet und Informationstechnologie
  • Software Engineer
  • Implementing a product feed management tool – Feed Rocket

    Feed Rocket imports product feeds from online shops to be easily optimized, customized and updated for different marketing channels

    Implemented: Developed architecture and implemented backend functionality from scratch to production in AWS for the company internal startup project. See the product: https://feedrocket.io

    Tech stack: Java, Hadoop, HBase, Mysql, Spring Boot, Hibernate, Git, ElasticSearch, AWS services, Docker, Jenkins
     


    Implementing a machine-learning-based eCommerce product classification system

    The system resides in the Hadoop cluster. Every day 80 million eCommerce products categorized automatically with ML algorithms

    Implemented:

    • Refactored core parts of the platform
    • ​​​ Redesigned the platform to make it more scalable and stable
    • The speed of categorization improved from 2-3 days to 0-1 days
    • Created a variety of tools to optimize the workflow of creating training data for ML models
    • Developed KPIs to track the performance of categorisation

    Tech stack: Java, Hadoop, HBase, Mysql, Caffe (deep learning library), LibSVM, LibLinear, Git


  • 11/2014 - 03/2015

    • Machine Discovery and Social Network Mining Lab. (Prof. Shou-De Lin) - National Taiwan University
  • Research assistant
  • Tasks: Research on active learning algorithms
    Tech stack: Matlab

  • 12/2011 - 04/2012

    • DataArt Solutions Inc. (dataart.com)
    • 250-500 Mitarbeiter
    • Internet und Informationstechnologie
  • Java Software Developer
  • Tasks: Web application development
    Tech stack: Java, JavaScript, CSS, HTML, Oracle

  • 06/2009 - 12/2011

    • VORONEZHSTALMOST GmbH
    • 1000-5000 Mitarbeiter
    • Industrie und Maschinenbau
  • Oracle Software developer
  • Tasks: Implementing required functionality on the corporate platform (ERP system)

    Developing data management tools and processes connected with the manufacture (stock management, workflow management, manufacturing processes management, financial transactions management). I was responsible / have performed the following tasks:

    • Development of reports using Crystal, Excel, Word

    • Development of complex SQL queries (i.e. using various joins and subqueries), stored procedures and pipeline functions

    • Using complex expressions to calculate, group, filter, parametrize and format the contents of reports

    • Implementing business logic using PL/SQL and Java

    Tech stack: Oracle DB, SQL, PL/SQL, Java


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