Data Engineer

Is this you?

Titan Operating System S.L. (Titan OS), the Barcelona-based technology, entertainment, and advertising company, is looking for you!

Our platform combines content discovery and advertising technology in one solution, helping leading TV brands unlock greater value. Titan OS powers devices from major brands including Philips, AOC and JVC, reaching millions of viewers across Europe and LATAM. Titan OS is also powering free premium FAST Channels on selected SONY Android TVs.

Over the last two years, Titan OS has grown revenue 10x and attracted leading investors, including Highland Europe and Mangrove.

At TitanOS, we live by three core values:

• Make things happen - We take ownership, move fast, and deliver impact
• No ego - We collaborate with respect and humility to reach shared goals
• Show genuine passion - We love what we do and never stop learning

Culture and environment are at the heart of our ethos. If the above resonates with you, keep reading because we believe you could be a perfect addition to our incredible team!

About the position

Titan OS  is looking for a Data Engineer to join our talented Data team in Barcelona.

In this role, you will play a crucial part in building and maintaining the data infrastructure that empowers our operating system to transform data into actionable insights. If you are passionate about data, have a strong technical skillset, and enjoy working in a collaborative environment, we encourage you to apply.

Key responsibilities

• Design and implement the integration of additional data solutions and pipelines

• Develop and maintain AWS infrastructure related to data ingestion and processing
• Optimize data management and processing, both in terms of budget and performance
• Work with stakeholders to identify root causes of inaccurate data points and develop fixes
• Design and implement Data Observability frameworks to monitor data health, schema drift, and pipeline performance, ensuring high reliability before data reaches downstream stakeholders.
• Standardize DataOps practices, including version control for data models, automated testing, and Infrastructure as Code (IaC) to streamline deployments.