Your mission

La información a continuación detalla los requisitos del puesto, la experiencia esperada del candidato y las cualificaciones correspondientes.

As an Intern in the Analytics & Insights Engineering team, you will primarily work on internal technical projects that strengthen Astrafy’s data stack and ways of working. Under the guidance of consultants and your entity manager, you will contribute to both the business and technical sides of these use cases, while investing heavily in learning and developing your skills. Depending on your progress and project needs, you may also have the opportunity to contribute to selected customer engagements under the supervision of experienced consultants.

You will also have the opportunity to use the latest AI technologies to support your day-to-day work on internal technical topics and accelerate how you learn, build, and deliver.

On the business side:
- Collaborate with internal stakeholders (consultants, Team Leads, product owners) to understand internal needs and priorities for our data and analytics stack.




- Help refine and clarify requirements for internal tools, dashboards, and processes to ensure they align with Astrafy’s business objectives.
- Assist in analyzing internal datasets (for example operational, financial, or product-related data) to identify opportunities for better reporting and decision-making.
- Support internal workshops or working sessions to define and validate key metrics (KPIs) used across teams.
- Contribute to the definition of visualizations and internal dashboards that make data easy to understand and use.
- Depending on your progress and the projects in flight, you may also be involved in specific, well-scoped client-related tasks, mainly as support to a consultant.

On the technical side:
- Contribute to building and improving internal data models in BigQuery and dbt that support Astrafy’s own reporting and analytics needs.
- Help develop and maintain LookML models and internal dashb

📌 Junior Analytics (Madrid)
🏢 Astrafy
📍 Madrid