Your Mission
This is a company built for growth. When you join exmox, you're stepping onto a global, highly competitive playing field, building high-performing consumer products in mobile gaming. We're scaling a rewarded user engagement and acquisition platform that helps publishers acquire and retain players.
As a Senior AI-Native Data Engineer (f/m/x), you'll operate at the intersection of data, engineering, and product, building and scaling the data foundation that powers our entire business. This isn't a role for maintaining pipelines or following predefined processes — we look for engineering mindset and entrepreneurial ownership: you build it, you own it, and you see the impact in production.
AI is not a side tool here, it's core to how you work: you'll use Claude and similar AI tools daily to plan, build, debug, and document, including managing context and memory across projects, integrating AI directly into your version control workflow, and running parallel agent workflows on separate tasks.
What You'll Own
- Data Pipelines & Integration: You design, develop, and maintain scalable ETL pipelines on Databricks to integrate data from various sources, including app and web products and marketing partner data.
- Data Lakehouse Ownership: You build and manage the Data Lakehouse on Databricks, including migrating legacy data products, and implement data transformations and processing logic using Databricks and PySpark.
- Monitoring & Optimization: You monitor and maintain the data stack for nightly and near-real-time processing of in-house tracking solutions.
- AI-Native Workflow: You use Claude and similar AI tools daily to plan, build, debug, and document your pipelines.
- Version Control & Worktrees: You integrate AI directly into your version control workflow, using Git worktrees to run several AI-assisted branches of work side by side.
- Context & Memory Management: You maintain structured project context for your AI tools, for example a CLAUDE.md-style instructions file.
- Parallel Agentic Work: You run multiple AI coding agents on separate tickets at the same time where it makes sense.
- Cross-Functional Collaboration: You work closely with engineering and ML teams to ensure seamless data flow and integration into the Data Lakehouse.
What You Bring
- Technical Foundation: Degree in Computer Science, Engineering, or Information Systems, or bootcamp experience, with a minimum of 4 years of professional experience in data engineering.
- Current, Deep Databricks Experience: Proficient in designing, implementing, and optimizing ETL processes on Databricks, with at least a year of current, hands-on depth.
- Tools & Technologies: Hands-on experience with Databricks and AWS services such as S3, Kinesis, and Lambda or similar technologies. Experience with GitLab CI/CD pipelines and familiarity with PostgreSQL are a plus.
- Genuine AI Fluency: You use AI tools like Claude hands-on, daily, across planning, building, debugging, and documentation.
- Programming Skills: Highly proficient in Python, SQL, and PySpark for data manipulation and processing.
- Mindset & Communication: Excellent problem-solving skills, strong attention to detail, fluent in English.
How We Win
Speed is the feature. Focus on the essential. See it. Own it. Solve it. Respect others.
Perks
Transport subsidy, learning budget, wellness and gym, workation, bi-weekly team lunches, and more.