data engineer for scalable data pipelines

Vention is a global engineering partner to tech leaders and fast-growing startups. Its data engineering teams help startups and enterprises turn data into smart decisions and better user experiences by building scalable data pipelines and infrastructure.

• Design, develop, and maintain scalable, reliable data solutions supporting business and analytical needs
• Build and enhance data pipelines for efficient data collection, transformation, and delivery across platforms and systems
• Manage large-scale datasets while maintaining data quality, consistency, and availability
• Collaborate with cross-functional teams to understand business requirements and deliver data solutions
• Optimize data processing workflows and improve platform performance, reliability, and scalability
• Support data platform modernization and continuous improvement initiatives
• Implement testing and validation practices to ensure data product accuracy and reliability
• Use AI-powered development tools and stay current with emerging technologies and engineering best practices to improve productivity, accelerate delivery, and drive innovation

• At least 3 years of Data Engineering experience delivering end-to-end data solutions
• Strong Python and SQL skills, including complex query development, data transformation, and performance optimization
• Hands-on experience building and maintaining data pipelines with Apache Airflow and working with large-scale datasets
• Experience with distributed data processing using Apache Spark and PySpark
• Understanding of data modeling and data warehousing, with practical Snowflake experience
• Experience with streaming and event-driven data platforms such as Apache Kafka
• Familiarity with modern data lake architectures and formats, including AWS S3, Iceberg, and Parquet
• Experience defining testing strategies, debugging issues, and ensuring the reliability and quality of data solutions
• English B2+
• Будет плюсом: Snowflake migration and modernization, including performance and cost optimization; Apache Airflow upgrades, migrations, or platform transformation projects; AI-assisted development practices and tools

• Expanded medical support for employees in Tashkent
• 19 Working days of vacation per year, increasing to 21 after two years with the company
• Corporate getaway and teambuilding activities
• Support for significant life events
• Referral bonuses for bringing in new talent
• Access to the EDU corporate community, with tech communities, interest clubs, events, a small R&D lab, a knowledge base, and a dedicated AI track
• Licenses for AI tools, including GitHub Copilot and Cursor