Lead Engineer/Data Engineer

Global FinTech Talent is working with a rapidly scaling FinTech organization based in Madrid looking for a technical anchor to own their entire data landscape. Because this role is central to the local leadership team, you must be based in Madrid and hold the full legal right to work in Spain.

This is a high-visibility position where you will be partnering with the C-level and functional heads to transform raw data into a competitive advantage. Strategic Ownership: Take full ownership of the data roadmap. You will transition the current setup into a scalable, enterprise grade data ecosystem.

Architect robust pipelines capable of handling hybrid data loads (batch and real-time streaming) from a complex web of internal microservices and external APIs.

You will work with Product, Finance, and Sales to design data models that solve actual operational problems.

Champion a "DevOps for Data" mindset implementing rigorous CI/CD, automated testing, and data governance standards.

You will mentor a talented squad of data engineers and analysts, conducting code reviews and elevating the team’s technical output.

Machine Learning Operations: Collaborate with Platform Engineers and Data Scientists to build the infrastructure required to run reliable ML models in production.

The Technical Toolkit To succeed, you need a background in modern data engineering within complex environments (Scale-ups or Enterprise).

Advanced proficiency in Python and SQL is mandatory. You should have deep experience with transformation and orchestration tools like DBT and Airflow. (Experience with Apache Spark is a strong plus).

Cloud Native Architecture: You must be an AWS native. We are looking for specific experience utilizing and warehousing components such as Redshift, Athena, Glue, and S3.

Infrastructure: Proven ability to manage infrastructure as code using Terraform.

Strong grasp of modern data architecture patterns (Data Lakes, Warehousing, Data Marts).

Proven Leadership: Previous experience as a Principal Engineer, Team Lead, or Head of Data is essential. You must have a solid understanding of financial principles and data accuracy.

Innovation: Exposure to AI/ML workflows and model deployment.