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Open nowPosted 7 days ago

Lead AI Data & Analytics Engineer

Stillfront25 open roles

Where
Hamburg, Germany
Work mode
Remote
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Your applicationOpen nowLead AI Data & Analytics EngineerStillfront · Hamburg, Germany
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The clock on this job

Early applications get read.

13.4% of postings close within 7 days. Measured by our own scanner across the market. Stillfront postings stay open a median of 15 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.6%3 days
  3. 13.4%7 days
  4. 21.6%14 days
  5. 36.2%30 days
  6. 59.0%60 days
This job: posted 7 days ago

Stillfront median: 15 days open

The posting

Build the Data Foundation for a New Mobile Game!

We're not looking for someone who has "built a dashboard". And we're not looking for someone who keeps an existing data stack running. We're looking for someone who already uses agentic workflows as a core part of how they work: Claude Code, Codex, Cursor, custom agents, MCP servers, skills, planning loops, review gates, and AI-assisted engineering. Someone with strong opinions on which AI workflows hold up in production and which fall apart when real decisions depend on the numbers.

This is a greenfield build. Our new mobile game is heading into launch, and there is no data warehouse yet. You will choose the stack, set it up, and build the analytics foundation from the first tracked event to the first board-level KPI, with agents as your team. You'll define how gameplay, monetization, attribution, and player behavior data are collected, structured, and transformed into trustworthy insights, automated reporting, and AI-powered analytics tools.

You will work at the intersection of AI, analytics, and game development, building the data foundation of a new game from scratch. You'll define its technical direction and drive the evolution of its analytics and AI capabilities from concept to production.

Unlike a traditional analytics role, you'll use agents to dramatically increase your throughput while remaining the architect, reviewer, and final owner of correctness. The agents generate volume; you provide judgement. If you have been waiting for the chance to design analytics the way it should work with agentic AI, instead of retrofitting AI onto a legacy setup, this is it.

YOUR MISSION

Build the Data Foundation

  • Design and operate the end-to-end gameplay analytics ecosystem.
  • Define tracking, storage, processing, and reporting architecture.
  • Own data correctness and make judgement calls when quality checks flag anomalies.

Drive AI-Native Analytics

  • 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.

YOUR BACKSTORY

  • You have built an analytics or data platform from scratch at least once: choosing the stack, setting up the warehouse and pipelines, and taking it into production. Running or extending an existing setup alone is not enough.
  • Several years of experience building analytics or data-driven systems in production environments, ideally in gaming or mobile.
  • Analytics experience on free-to-play mobile games, ideally including a launch (soft launch to global). You know what the data has to answer in the weeks around launch and UA scaling.
  • AI-first is how you already work today, not something you plan to learn. 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. You can show agentic analytics work you've shipped and used for real decisions.
  • 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. You bring the drive to build something new at high speed, and you push it forward without waiting to be asked.
  • Excellent English communication skills.
  • Passion for gaming.

Nice to have

  • Depth in monetization, economy, and LiveOps analytics.
  • 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.

HOW WE INTERVIEW

Expect to walk us through an agentic workflow you've actually built and used – the specs and context you feed it, how you structure the loop, where it breaks, how you catch it, and what you'd never let an agent do unsupervised on data people make decisions from. Bring screen-shares, repos, prompts, whatever shows the real thing. We're more interested in your judgement and battle scars than in polished slides.

Goodgame Studios is known for data-driven game development and successful live-service strategy titles. We self-publish our games in-house with all relevant disciplines under one roof. Our studio is based in Hamburg, Germany, and we welcome applications from international candidates. English is our working language. As part of Stillfront Group, one of Europe's leading game publishers with 200M+ registered players, an €1B+ in lifetime revenue, we work on long-term IP growth with a strong focus on execution.

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