Igor Gorbenko, Developer in Dubai, United Arab Emirates
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Igor Gorbenko

Verified Expert  in Engineering

Database and Back-end Developer

Dubai, United Arab Emirates
Toptal Member Since
October 18, 2021

Igor is a data engineer and cloud architect with nearly 13 years of solid experience building high-load reliable systems, DWH, ETL, and machine learning pipelines for Gazprombank, Stanford, GlaxoSmithKline, Fujitsu, AbbVie, and Royal Mail. He is a cloud-agnostic engineer specializing in Flask, FastAPI, and database integration. Igor is also keen on building GCP-based systems to leverage businesses to work more efficiently, gain more flexibility, and allow a strategic advantage.


Google Cloud Platform (GCP), Redis Clusters, Google Bigtable, Cloud Dataflow...
EPAM Systems
Scala, Apache NiFi, Apache Kafka, Pub/Sub, Machine Learning...
Amazon Web Services (AWS), Apache Spark, Machine Learning, Redshift, Terraform...




Preferred Environment

PyCharm, Slack, Linux, Git

The most amazing...

...recommendation system I've developed is one of the world's most popular video streaming platforms, Tango Live.

Work Experience

Big Data Architect and Team Lead

2021 - PRESENT
  • Designed a highly loaded recommendation system as the main component of an app.
  • Developed pipelines for training machine learning models and orchestration of their call.
  • Created a mechanism for monitoring the operation of all components of the recommendation system.
  • Optimized data loading into storage, refactoring the legacy code.
Technologies: Google Cloud Platform (GCP), Redis Clusters, Google Bigtable, Cloud Dataflow, Google BigQuery, Machine Learning Operations (MLOps), Apache Airflow, GitLab, Docker, Machine Learning

Key Big Data Developer

2020 - 2021
EPAM Systems
  • Designed an apartment's interior design recommendation system.
  • Developed the back-end part of the flat interior recommendations system, including a scraper for collecting information for training models and all data processing processes.
  • Solved incidents reported on Jira related to data pipelines.
Technologies: Scala, Apache NiFi, Apache Kafka, Pub/Sub, Machine Learning, Google Cloud Platform (GCP), SQL

Big Data Architect

2019 - 2020
  • Migrated anomaly calculation processes from Docker containers to an EMR Apache Spark cluster. This allowed optimizing the speed of calculations several times.
  • Reduced in several-fold the cost of using AWS due to dynamic calculation EMR cluster configuration.
  • Developed the monitoring system with reports and alerts mechanisms. Implemented the CI/CD process.
  • Performed tech leadership for the cloud-based prediction system design.
Technologies: Amazon Web Services (AWS), Apache Spark, Machine Learning, Redshift, Terraform, Amazon DynamoDB, Amazon Cognito, Dropbox API, Google APIs, Docker

Lead Big Data Developer

2018 - 2019
First Line Software
  • Developed the full cycle of the ETL process for transforming customers' raw data into the OMOP Common Data Model (CDM) standard.
  • Developed and implemented a tool to automate data conversion using Python, SQL, and Spark.
  • Created and executed a tool for visualizing the converted data with Python, Django, and JavaScript.
Technologies: Amazon Web Services (AWS), Google Cloud Platform (GCP), Apache Spark, SQL, Google BigQuery, Redshift, Django, Docker

Senior Software Developer

2016 - 2018
Fujitsu Global
  • Developed a system for distributing tickets by the performer of incidents.
  • Developed and implemented a tracking system on the project.
  • Migrated the billing reporting system to SQL Server Reporting Services (SSRS).
Technologies: SQL, Bash, Linux, Microsoft SQL Server, IBM Informix, C#.NET, Oracle

Chief Software Engineer

2011 - 2016
  • Developed an analytical and management reporting system.
  • Developed an automated system for installing retail exchange rates. This system increased the bank's income by several times from currency exchange operations to reduce currency risks.
  • Created a system for planning and monitoring the execution of the plan.
  • Built a system for combating fraudulent transactions through the "Client Bank" functionality.
Technologies: SQL, Excel VBA, C#.NET, Microsoft SQL Server, Investments, Stock Market

Recommendation System for Tango

A GCP-based system for the purpose of recommendation. This system allows users to receive the most relevant content based on their interests.

I was the engineering team leader and owned the entire development process on the data and cloud sides.

An Apartments' Interior Design Recommendation System for EPAM

A GCP-based recommendation system. The system of recommendations for the interior design of apartments offers the most optimal arrangement of furniture based on a given apartment plan.

I was a project architect, as well as a data engineer and back-end developer. I designed the architecture of the system and the interaction of all components.

A Complex ETL of Medical Data with a Custom Conversion Kit for First-line Software

The main task of this project was to convert raw data into a standardized format. The original datasets could be of various types and stored in different storages, such as AWS S3, GCP GCS, Hadoop HDFS, PostgreSQL, Amazon Redshift, and more. The project needed a tool to prepare a conversion in automatic mode and minimize the issues during the ETL process with Spark SQL.

I was a tech lead on this project. My responsibilities were developing the core part of the framework’s components using Python, which allowed us to automate scheduled ETL steps and run other tasks after conversion, such as unit tests, stats reports, and so on. I also performed code reviewing and ran the ETL pipelines.


SQL, Bash, Python, Scala, C#.NET, Excel VBA


PyCharm, Git, Apache Beam, Apache Airflow, Postman, Slack, Grafana, Terraform, Amazon Cognito, Cloud Dataflow, GitLab, Apache NiFi, Google Kubernetes Engine (GKE), BigQuery, Spark SQL, Amazon Athena, Google Cloud Dataproc


REST, ETL, Database Design


Linux, Amazon Web Services (AWS), Google Cloud Platform (GCP), Docker, Apache Kafka, New Relic, Oracle, Kubernetes


PostgreSQL, Microsoft SQL Server, Data Pipelines, JSON, Databases, Redshift, Google Bigtable, Amazon DynamoDB, IBM Informix, Cloud Firestore


IT Systems Architecture, Big Data, Big Data Architecture, Data Architecture, Data Engineering, FastAPI, Redis Clusters, Machine Learning Operations (MLOps), Machine Learning, Google BigQuery, Pub/Sub, Investments, Stock Market, Google Cloud Functions, Cloud Run


Flask, Apache Spark, Django, Locust


Dropbox API, Google APIs

2003 - 2008

Master's Degree in Information Technologies

Kazan National Research Technical University - Kazan, Russia


AWS Certified Solutions Architect Associate



Professional Cloud Architect

Google Cloud


Professional Data Engineer

Google Cloud


Associate Cloud Engineer

Google Cloud


AWS Certified Developer



AWS Certified Cloud Practitioner


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