> Markdown version of [/jobs/ext/2893997-ai-data-analytics-engineer](https://www.wearedevelopers.com/jobs/ext/2893997-ai-data-analytics-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Data & Analytics Engineer - **Company:** Goodgame Studios - **Location:** Hamburg, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Video Game Development, Python (Programming Language), Mobile Analytics, Standard Sql, Data Streaming, Cloud Platform System, Large Language Models, Reliability of Systems - **Published:** September 14, 2026 - **Apply:** https://startup.jobs/senior-ai-data-analytics-engineer-goodgame-studios-10058064 ## About the Role * Several years of experience building analytics or data-driven systems in production environments, ideally in gaming or mobile. * Deep comfort with LLMs, agents, and AI-assisted engineering workflows in production environments. * Hands-on experience using agentic workflows and AI coding tools in real-world projects. * The ability to discuss concretely how you: + structure prompts and context, + manage autonomous and multi-agent workflows, including when to intervene, + use MCP servers, custom tools, skills, or subagents, + review AI-generated code and queries without becoming a bottleneck. * Strong experience working with behavioral, transactional, or event-based datasets and deriving actionable insights from complex data. * Strong Python and SQL skills. You read and own code you did not write and verify outputs independently rather than blindly trusting generated results. * Experience designing scalable data architectures, pipelines, data models, dashboards, analytical frameworks, or automated insight-generation systems. * Familiarity with cloud-based data platforms and storage. * Strong analytical decomposition skills and the ability to translate ambiguous business questions into precise analytical problems. * Strong instinct for data quality, system reliability, and independent verification. You don't simply accept whatever the agent produces. * Comfortable operating independently, driving technical initiatives from concept to production, and owning outcomes rather than tasks. * Excellent English communication skills. * Passion for gaming. NICE TO HAVE * Gaming or mobile analytics experience (monetization, attribution, retention, LiveOps, economy). * Event-driven and streaming data architectures. * Real-time telemetry or anti-cheat / anomaly-detection systems. * Published or shared work on agentic workflows - blog posts, OSS subagents/skills, internal tooling you've open-sourced. ## Description * Build the semantic layer that translates raw gameplay data into validated gameplay and business concepts. * Develop AI-driven automated reporting, dashboards, and insight-generation workflows. * Evaluate and implement AI tools, agents, and workflows that improve analytics speed, reliability, and depth. * Review AI-generated code and analytics on critical paths before they reach production. Generate Product Intelligence * Identify opportunities, risks, anomalies, and trends across gameplay and player behavior. * Support product, balancing, design, and leadership teams with data-driven recommendations. * Translate complex datasets into clear, actionable insights. Set the Agentic Bar * Help define how the wider engineering organization adopts agentic practices. * Establish standards for tooling, review processes, quality gates, and what "done" means when agents generate most of the implementation. ## Related Videos - [How Data is Shaping our Games](https://www.wearedevelopers.com/videos/176-how-data-is-shaping-our-games) - [How building an industry DBMS differs from building a research one](https://www.wearedevelopers.com/videos/768-how-building-an-industry-dbms-differs-from-building-a-research-one) - [How to Build a Monetization Strategy Based on User's in-app Behavior](https://www.wearedevelopers.com/videos/174-how-to-build-a-monetization-strategy-based-on-user-s-in-app-behavior) - [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [How AI is shaping our games](https://www.wearedevelopers.com/videos/995-how-ai-is-shaping-our-games) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [John Romero - What AI Can, Can’t, and Shouldn’t do for Games](https://www.wearedevelopers.com/magazine/478-john-romero-what-ai-can-can-t-and-shouldn-t-do-for-games) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)