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# Engineer or Applied Data Scientist

- **Company:** Gitkraken
- **Location:** Spain
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Computing, Data Warehousing, Cursor (Graphical User Interface Elements), Programming Tools, Monitoring of Systems, Python (Programming Language), Machine Learning, Operational Data Store, TypeScript, Datadog, Large Language Models, Snowflake, Backend, Enterprise Integration
- **Published:** August 11, 2026
- **Apply:** https://es.trabajo.org/oferta-4021-ad834c97330244684a800d5c8c501849

## About the Role

Data & Infrastructure: Snowflake for data warehousing, AWS for cloud infrastructure, and Datadog for monitoring and observability. - AI Ecosystem & DevEx: We live and breathe developer experience. We heavily leverage and build around modern AI development tools and LLMs like Cursor, Claude Code, and Codex to accelerate execution and shape the future of workflows. What We're Looking For - Deep experience in machine learning, applied AI, or a similarly hands-on product data role at a Senior level - A track record of shipping data or ML-powered capabilities into real products or operational workflows - Comfort moving from messy problem statements to practical execution without a lot of structure - Ability to work across the stack, not just in notebooks - Strong product judgment and a bias toward simple solutions that deliver measurable value -, Experience deciding whether a problem is best solved with ML, rules, analytics, automation, or workflow

## Description

opportunities from product, customer, and operational data - Build practical 80/20 solutions that create leverage quickly, then refine them based on traction - Own end-to-end execution across data exploration, modeling, experimentation, backend integration, and productization - Partner with engineering, product, design, and leadership to turn rough ideas into shipped capabilities - Use ML, analytics, heuristics, and automation pragmatically rather than forcing a model where one is not needed - Define success metrics, instrument outcomes, and improve solutions based on real-world usage - Help shape how GitKraken uses AI and data to improve developer workflows, team velocity, and product experience Our Tech Lens We value strong fundamentals over a rigid checklist and are always open to adopting new technologies, here is a snapshot of our current ecosystem: - Languages: Python (for data/ML execution), alongside Go and TypeScript across our core product and backend environments. -