Senior Data Engineer

VYBS is the fastest-growing loyalty platform in mobile gaming, a $100B+ market with over 3 billion players. Millions of players use our app to discover games and get rewarded for playing them, and hundreds of game studios use us to reach their most valuable players.

The role. You'll join the data engineering team, owning the data platform that runs VYBS: the pipelines that capture every player action, the warehouse the whole company works from, and the data behind our AI models and business decisions. You'll design the architecture, set the standards, decide what ships, and build the agentic factory that implements it.

Why this is a great data engineering role

• Data is the core of the product. In gaming, data decides what players see, what they earn, and what advertisers pay. The data you build is what the business runs on.
• Short feedback loops. We have a large, active player base, so the data you deliver drives decisions and product changes within days.
• Real technical depth. The work includes massive-scale event pipelines, feature data for AI models in production, and data flowing to and from the largest brands in the industry.
• You build the system that builds the software. Instead of boilerplate, your time goes to data architecture, modeling, trade-offs, and the AI engineering system itself. This is where software engineering is heading, and you'll be doing it now.
• Ownership. R&D is a small, senior team with light process, and engineers have a real say in architecture.

What you'll do

• Own the data pipeline that processes billions of behavioral events a day from across the mobile gaming industry.
• Design the data models and metrics layer that the whole company, and its AI agents, rely on to understand the business.
• Build the agentic factory that implements, monitors and maintains the data infrastructure.

What we're looking for

• 5+ years of hands-on data engineering, including high-volume pipelines you built and ran in production.
• Strong data modeling and SQL, with experience designing models that are efficient and reliable.
• Strong Python engineering skills: clean, tested, maintainable code.
• Experience with a cloud data warehouse such as Snowflake, BigQuery or similar.
• Advantage: experience building agentic software factories, meaning setups where AI agents build, monitor and maintain systems.
• Advantage: experience in adtech, gaming or high-traffic B2C, or with data for ML models.