Our aim is to keep doing so for many more years, if not decades. In order to be able to do so, we’ve defined a distinct way of how we’re working at Wooga, so that all relevant aspects intertwine and have a positive impact on the game. No matter if you’re part of a game team or support the success of Wooga as part of a central team, all 250+ employees from around the world can make an impact. We’re proud of the environment we’ve built, and believe you’ll enjoy working with some of the best people in the industry.
Our drivers: Speed, Focus, Ownership, and Impact, guide our working style at Wooga and help us make a deliberate choice to focus on what is important to us, while working towards a shared goal.
These drivers shape how we work together and what we expect from ourselves and our leaders.
We are looking for a high-impact, proactive Senior Data Engineer to join our Data Engineering team in Berlin. In this role, you won't just build pipelines—you will architect the data foundation that powers our next generation of casual games and advanced analytics, and AI-driven workflows. You will be in an environment where you can take full ownership of business outcomes, bridge technical execution with strategy, and proactively identify opportunities to optimize and scale our data transformation journey.
- Data Architecture & Strategy: Design and build resilient, scalable data infrastructure optimized for analytical workflows, feature stores, real-time context delivery, and AI-ready, well-documented data for agents and LLM applications.
- Modern Pipeline Engineering: Build, maintain, and optimize robust batch and streaming ETL/ELT pipelines using Scala, Python, SQL and dbt.
- Data Warehousing & Lakehouse: Architect clean, cost-efficient, and highly performance schemes across our cloud data warehouse platform on Snowflake.
- AI-Enabled Engineering & Agentic Workflows: Use AI as a daily force multiplier, not only for writing code but across the data lifecycle, from design and documentation to testing, debugging, and incident triage. Design, build, and operate agentic workflows (for example, agents that monitor pipelines, investigate data quality issues, generate and validate dbt models, or answer analysts’ questions against governed data), with proper guardrails, evaluation, and observability.
- Quality, Reliability & Governance: Implement automated testing, observability, and monitoring frameworks to guarantee high data reliability and low latency.
- Engineering Excellence & Best Practices: Follow rigorous CI/CD practices, Infrastructure-as-Code (Terraform), version control, and clear documentation across all data assets.
- Cross-Functional Enablement: Collaborate closely with marketing managers, game teams, product managers, and data analysts to turn ambiguous business needs into high-impact data solutions.