Data is at the core of every product decision we make. In this role, you’ll help shape and scale the data ecosystem behind products used by millions of users across international markets. You’ll work on high-volume data platforms, build reliable pipelines, and create the foundation that enables analytics, business intelligence, and data science teams to make fast, data-driven decisions. This is an opportunity to solve complex engineering challenges, optimize large-scale data systems, and directly influence the way data powers our products and business growth
In this role, you will
Design and develop scalable, cloud-native data architectures in BigQuery, ensuring optimal performance, maintainability, and cost efficiency
Build, automate, and maintain ETL/ELT pipelines using modern data stack tools and custom solutions
Create and optimize business-critical data marts, aggregations, and analytical datasets for reporting, dashboarding, and product insights
Implement data quality frameworks, monitoring systems, logging, and alerting mechanisms to ensure data reliability
Continuously improve performance, scalability, and cost efficiency of production data infrastructure
Partner closely with Data Science teams to build reliable data services, infrastructure, and pipelines supporting machine learning and advanced analytics initiatives
Collaborate with product, analytics, and engineering teams to define and deliver scalable data solutions across the organization
It’s all about you
3+ years of experience as a Data Engineer working with large-scale data platforms and high-volume datasets
Strong expertise in data modeling, data warehousing concepts, and analytical data architecture design
Proven experience designing and developing complex ETL/ELT workflows following BI and data engineering best practices
Hands-on experience with BigQuery, including partitioning, clustering, query optimization, and cost management
Strong SQL skills with the ability to write and optimize complex analytical queries using Google SQL
Proficiency in Python and data processing libraries such as Pandas and PySpark
Experience working with ClickHouse, including architecture understanding, performance optimization, and migration approaches
Solid knowledge of Google Cloud Platform services, including Cloud Storage, Pub/Sub, DataForm, IAM, and service accounts
Experience with Git, CI/CD practices, automated deployments, and environment management for data workflows
Strong understanding of monitoring, logging, data validation, and production-grade data quality practices
Excellent analytical thinking, problem-solving skills, and ability to work independently in a fast-paced environment
Strong communication and collaboration skills with both technical and non-technical stakeholders
Understanding of product metrics, experimentation frameworks, and data-driven decision making
2+ years of previous Software Engineering experience
Experience optimizing storage and compute resources to improve infrastructure efficiency and reduce operational costs
Experience integrating data platforms with BI tools such as Tableau or Looker
Would be a plus
Familiarity with supporting machine learning workflows and data infrastructure for Data Science teams
Experience working with AI-powered development tools, including Claude Code, Claude Agents, or similar AI-assisted engineering solutions
What we offer
Care and support:
20 paid vacation days, 15 sick days, and 6 additional days off for family events
Up to 10 additional days off for public holidays
100% medical insurance coverage
Sports and equipment reimbursement
Team building events, corporate gifts, and stylish merch
Maternity Recovery Support Allowance
Financial and legal support
Position retention and support for those who join the Armed Forces of Ukraine
Participation in social initiatives supporting Ukraine
Comfortable working environment:
Work from our Kyiv hub or remotely with a flexib
