Data engineer in payment systems

Paynet is a leading payment system in Uzbekistan, offering innovative and convenient solutions for everyday financial transactions for individuals and businesses. Founded in 2005, the company has become an integral part of the country’s financial ecosystem, providing a wide range of services through a network of terminals and a mobile application.

• design, build, and maintain scalable data pipelines and ETL processes to support payment processing and analytics across Paynet’s platforms.
• developing and optimizing data models and data warehouse structures to ensure high data quality, performance, and reliability.
• collaborate with software engineers, analysts, and business stakeholders to integrate data from multiple sources, enable reporting, and support data-driven decision-making.
• monitoring data workflows
• troubleshooting issues
• improving data security and governance practices
• contributing to the enhancement of Paynet’s data architecture

• Strong Data Engineering skills, including building and maintaining scalable data pipelines and data integration workflows.
• Experience with Data Modeling and Data Warehousing to design efficient, reliable, and well-structured data repositories.
• Proficiency in Extract Transform Load (ETL) processes and tools to ingest, transform, and load data from diverse sources.
• Capability in Data Analytics to support reporting, performance monitoring, and data-driven insights for business stakeholders.
• Hands-on experience with SQL and at least one programming language commonly used in data engineering (such as Python).
• Familiarity with relational and NoSQL databases, as well as modern data platforms
• Understanding of data security, data governance, and best practices for handling sensitive financial information.
• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field, or equivalent practical experience.
• Ability to work collaboratively in an on-site environment, communicate clearly, and adapt to a fast-paced fintech setting.

• This is a full-time, on-site Data Engineer role