Analytics Engineer I - AI & Data Enablement at DeliveryHero

We are looking for an Analytics Engineer I to join Data Enablement, our team focused on building reliable data foundations and enabling the next generation of data products at Glovo. This is an entry-level role for someone who wants to grow in Analytics Engineering while developing strong foundations in AI-enabled data work. This is not a pure AI Engineer role, but we are looking for someone who is already AI-savvy and has practical experience using AI tools to improve their work. We expect the candidate to understand both the value and the limitations of AI-generated outputs.  As part of DataX, you will help us make data more accessible, reliable and useful for business teams, while progressively contributing to initiatives involving AI-assisted workflows, data quality, documentation, automation support and GenAI-enabled data experiences. You will work closely with Data Analysts, Product Managers, Business stakeholders and other Data teams to understand problems, build trusted data assets and support the responsible use of AI in data work. You will: • Support the development of reliable datasets, data models and analytical assets used by business and technical teams. • Work with more senior engineers to understand business requirements and translate them into simple, well-defined data solutions. • Write, test and maintain SQL transformations with a strong focus on quality, readability and documentation. • Help validate data outputs and ensure they are accurate, understandable and fit for purpose. • Apply your existing AI literacy to real Analytics Engineering use cases, including prompt design, context grounding, hallucination risks, human validation and responsible AI usage. • Contribute to internal knowledge bases, documentation and best practices that help teams use data and AI-enabled tools safely. • Collaborate with stakeholders to understand repetitive pain points, manual processes and opportunities where better data products can improve decision-making. • Learn and apply engineering best practices around version control, testing, monitoring, data quality and access control. • Grow into an autonomous Analytics Engineer capable of owning small data products and contributing to AI-enabled data initiatives.