Senior AI-Native Data Engineer (f/m/x)

• Technical Foundation: You have a 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: You are proficient in designing, implementing, and optimizing ETL processes on Databricks, with at least a year of current, hands-on depth, not brief or dated exposure.
• Tools & Technologies: You have 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, not just for occasional testing. This is a core, non-negotiable part of the role, not a nice-to-have.
• Context Engineering: You know how to set up and maintain project context and memory for AI coding tools, structured instructions and reusable prompts, so they stay effective as a codebase grows rather than relying on default settings.
• Agentic & Worktree Fluency: You're comfortable running several tickets in parallel with AI assistance, using Git worktrees or a similar approach to keep parallel AI-assisted branches isolated and reviewable, and you can explain your actual workflow in detail rather than describing it as something that just happens automatically.
• Programming Skills: You are highly proficient in Python, SQL, and PySpark for data manipulation and processing, and you write clean, maintainable, production-ready code.
• Mindset & Communication: You have excellent problem-solving skills, strong attention to detail, and the ability to work independently and collaboratively. You are fluent in English, both verbally and in writing, comfortable letting AI take on a meaningful share of day-to-day coordination, and genuinely open to a way of working where AI reshapes how data teams operate, not just tolerant of it.

How We Win

• Speed is the feature. Speed beats rocket science. We move fast, test fast, and multiply our pace with AI, because action creates information and small wins compound. A fast failure is a lesson we learn from, a slow one is a problem we can't afford.
• Focus on the essential. Done is better than perfect. We stay focused on what actually moves us forward and protect people's time from anything that doesn't. We're direct in how we communicate too, no rambling, no unnecessary detail.
• See it. Own it. Solve it. The first to see it is best placed to fix it. We're not a place for comfort, we're a place for doers. “Not my job” isn't in our vocabulary, if you spot something, you help make sure it gets solved.
• Respect others. Trust multiplies. Respect is non-negotiable. We disagree with ideas, never with people. Trust here is built the same way it is anywhere, through consistency, a thank you, a moment of listening, and owning your mistakes.
• Perks that help you focus on what matters. Transport subsidy, learning budget, wellness and gym, workation, bi-weekly team lunches, and more. The perks are great, but the real reason people join and stay is the challenge, the ownership, and the drive to win together.

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