About Simply.TV At Simply.TV, we're redefining how the world experiences TV metadata. As a leading provider of advanced, AI-driven metadata solutions, we empower broadcasters, streaming platforms, and telecom operators to deliver smarter, more engaging content discovery experiences. From next-gen EPG (Electronic Program Guide) data to rich content enrichment, we enable our partners to stay ahead in a rapidly evolving media landscape.Headquartered in Copenhagen, but supported by 450+ employees worldwide, our data fuels user interfaces used by millions of viewers every day — and we’re just getting started. Whether you're passionate about media technology, data engineering, or product innovation, Simply.TV is the place to shape the future of TV — and have fun doing it.Join us, and let’s make content discovery simple, powerful, and inspiringThe RoleAs part of the Ingest team, you will play a key role in ensuring our TV, movie, and series data flows smoothly, accurately, and efficiently from multiple sources into our systems. This internship is adecuado for detail-oriented,



problem-solving individuals who enjoy working with data pipelines, scheduling systems, and supporting both internal and external stakeholders. This is a paid internship. Important: This role requires the candidate to be fluent in Spanish from Spain. ResponsibilitiesImplement and update hardcoding rules for parsers.Fix issues with existing parsers and optimize them for new content sources.Set up new parsers as needed for incoming data streams.Investigate and resolve internal data complaints.Monitor data health and ensure datasets are accurate, complete, and consistent.Check schedules for failures and report issues.Collaborate with the development team to resolve scheduling problems.Optimize how schedules are set up to ensure smooth operations.Support ManagementRespond to customer support cases within SLA times.Ensure internal stakeholders receive timely support and issue resolution. Why join? Work at the

📌 Ingest Intern (Madrid)
🏢 Simply TV
📍 Madrid