Georgii is available for hire
Hire GeorgiiGeorgii Chelidze
Verified Expert in Engineering
Data Engineer and Developer
Tbilisi, Georgia
Toptal member since May 22, 2026
Bio
Georgii is a senior data engineer with more than eight years of experience building scalable data platforms, real-time pipelines, and AI and machine learning systems. He specializes in Python, SQL, Spark, and Kafka, with deep expertise in AWS, lakehouse, and data warehouse architecture, and end-to-end data governance. His work spans fintech and enterprise environments, where he delivers production-ready data solutions that are built to perform at scale.
Portfolio
Samsung Food
ClickHouse, Python 3, Apache Airflow, Data Build Tool (dbt), Kubernetes, dltHub...
Bank of Georgia
Python 3, PySpark, Hadoop, Apache Kafka, Kubernetes, Python...
Bank of Georgia
Python 3, PySpark, Hadoop, AWS IoT, Apache Airflow, Spark Structured Streaming...
Experience
- Python 3 - 9 years
- SQL - 8 years
- Apache Airflow - 7 years
- Data Governance - 6 years
- PySpark - 5 years
- Apache Kafka - 4 years
- ClickHouse - 3 years
- Spark Structured Streaming - 3 years
Preferred Environment
Python 3, SQL, PySpark, Apache Airflow, Apache Kafka, Data Build Tool (dbt), ClickHouse, Docker, Hadoop, AWS IoT
The most amazing...
...solution I've built is a data lakehouse and streaming platform that made enterprise data faster, better governed, and ready for AI.
Work Experience
Data Platform Manager
2025 - 2026
Samsung Food
- Built Python-based DataOps tooling to automate pipeline deployment, schema validation, and governance workflows, improving developer productivity—published as dg-kit on PyPI.
- Designed scalable Data Vault and star schema models using Oracle Data Modeler, enforcing governance practices across data quality, lineage, and PII compliance.
- Developed a data integration and transformation stack using dltHub and dbt.
Technologies: ClickHouse, Python 3, Apache Airflow, Data Build Tool (dbt), Kubernetes, dltHub, Docker, Python, Amazon Web Services (AWS), Amazon S3 (AWS S3), Data Engineering, Data Modeling, Dimensional Modeling, Data Warehousing, ETL
Data Engineering Manager
2024 - 2025
Bank of Georgia
- Led and mentored a diverse team of engineers and BI developers, ensuring the successful delivery of complex projects.
- Oversaw the development and implementation of scalable data solutions that support the organization's strategic goals.
- Collaborated with cross-functional teams to design and architect robust data infrastructure and solutions.
- Drove innovation and best practices in data management, big data processing, BI development, and solution architecture.
Technologies: Python 3, PySpark, Hadoop, Apache Kafka, Kubernetes, Python, Amazon Web Services (AWS), Amazon S3 (AWS S3), AWS Glue, Data Engineering, Data Modeling, Dimensional Modeling, Data Warehousing, ETL
Head of Data Engineering and Analyses
2023 - 2024
Bank of Georgia
- Managed multiple competencies, including AI engineering, machine learning engineering, big data engineering, data engineering, and BI development.
- Expanded the team from 38 to 54 members, ensuring a robust and skilled workforce.
- Oversaw projects such as lakehouses, ML models, and chatbots, driving innovation and efficiency.
- Introduced a system-to-system data feeding approach for data-intensive applications and established a dedicated team.
- Contributed to the architecture of the lakehouse and developed code for the system-to-system feeding application.
- Outlined the software development lifecycle, including environments and code lifecycle in those environments, branching strategy, local development in Docker, test-driven development, and general frameworks for reusable components.
- Hired top talent from the market and competitors, enhancing the team's capabilities.
- Managed interpersonal and behavioral issues, fostering a positive and productive work environment.
- Mentored several team members, providing guidance and support for their professional growth.
- Played a key role in organizational architecture during the transition to a tribes structure, introducing guilds and authoring a handbook on creating and managing guilds.
Technologies: Python 3, PySpark, Hadoop, AWS IoT, Apache Airflow, Spark Structured Streaming, Apache Kafka, Redis, Kubernetes, Python, Amazon Web Services (AWS), Amazon S3 (AWS S3), AWS Glue, Data Engineering, Data Modeling, Dimensional Modeling, Data Warehousing, ETL
Senior Data Engineer
2022 - 2023
Innotech
- Collected ATM data from different network levels and brought it into the bank's internal network.
- Provided data quality, built data marts, searched for insights, and created add-on value from data.
- Participated in the creation of a model that predicts cash-out demand in ATMs.
Technologies: Python 3, Docker, Bash, Apache Hive, Hadoop, PySpark, Jupyter, ActiveMQ, Python, AWS Glue, Data Engineering, Data Modeling, Dimensional Modeling, Data Warehousing, ETL
Leading Expert in Technologies
2020 - 2022
Sberbank
- Established standards for gathering business requirements, designing to-be processes in BPMN notation, and conducting as-is analysis.
- Settled a clear definition of done requirements for all stages of report development from the system analyst's perspective.
- Designed, developed, and implemented a process of data correction and recalculation of all dependent reports. Brought three reports to prom processing, handling over 1.4 billion transactions daily.
Technologies: Oracle, Hadoop, Apache Hive, Apache Impala, Apache Kafka, Python, Data Engineering, Data Modeling, Dimensional Modeling, Data Warehousing, ETL
Data Analysis Supervisor
2019 - 2020
DOM RF
- Developed reliable, fault-tolerant, scalable data flow from the federal housing web service to the analytical data mart.
- Pioneered data science practices and maintained infrastructure.
- Built and administered a PostgreSQL database, also serving as admin for Tableau Server.
- Delivered a housing sector monitor to the government at the start of the COVID pandemic, as part of a cross-functional team.
- Monitored the level of industry monopolization in regions based on the Hirschman index.
Technologies: ClickHouse, PostgreSQL, Python 3, Apache Airflow, Tableau, Ubuntu, Bash, Python, Data Engineering, Data Modeling, Dimensional Modeling, Data Warehousing, ETL
Experience
Data Governance Kit
https://github.com/chelgd/dg_kitdg_kit provides programmatic access to governance metadata across logical, physical, and data catalog models. It is designed for CI checks, governance automation, and metadata synchronization workflows.
Education
2012 - 2016
Bachelor's Degree in Finance and Financial Services
University of Westminster - London, England
Skills
Libraries/APIs
PySpark
Tools
Apache Airflow, Apache Impala, AWS Glue, Tableau, Jupyter, ActiveMQ, dltHub, Oracle SQL Data Modeler
Languages
Python 3, SQL, Python, Bash
Frameworks
Hadoop, Spark Structured Streaming
Paradigms
Dimensional Modeling, ETL
Platforms
AWS IoT, Ubuntu, Apache Kafka, Docker, Amazon Web Services (AWS), Oracle, Kubernetes
Storage
ClickHouse, PostgreSQL, Apache Hive, Amazon S3 (AWS S3), Redis
Other
Data Build Tool (dbt), Data Governance, Data Engineering, Data Modeling, Data Warehousing, Basel
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