Senior Data Engineer

Description

The company uses data to guide its growth plan, and this role helps build the base for data-driven decisions across the business.

You would join the Data Engineering team, which sits within a Data team that also includes Data Scientists, Analytics Engineers and Data Analysts. The team is building and maintaining a large-scale Data Platform.

The company offers business accounts, hedging and financing on one integrated platform. It was founded in 2009, is a fast-growing fintech with 2000+ staff across nearly 70 cities, and its core product helps businesses manage global cash flow.

Hybrid, Madrid office: 4 days in the office and 1 day working from home.

The company welcomes diverse backgrounds and does not tolerate discrimination.

Applicants should only expect contact from an company's site address. The company never asks for payment during recruitment. Recruitment agencies and search firms are addressed in a separate notice.

AI and automated tools are used only for administrative tasks in recruitment. Human recruiters and hiring managers make all hiring decisions.

Responsibilities

• Design, deploy and maintain reliable ELT and ETL pipelines that pull from transactional databases, REST APIs and file-based sources.
• Work with others to design scalable data models that deliver clean, structured data for BI tools and team-level decisions.
• Run orchestration with Apache Airflow on GCP Cloud Composer, and use GCP services such as Cloud Run, GKE, Cloud Functions and Artifact Registry.
• Apply software engineering practices such as version control, CI/CD, testing and code review, and work to reduce technical debt.
• Automate end-to-end data workflows so that teams across the company no longer need manual extracts.
• Help put data quality standards, access controls and governance policies in place across the platform.
• Current stack: Google Cloud Platform, Apache Airflow, dbt and dbt Cloud, Docker, Cloud Build, Looker and Looker Studio, GitHub, Jira, Hevo Data, and Synq or DataHub.

Requirements

• 3+ years of data engineering experience, including building, maintaining and tuning pipelines in big data environments.
• Strong Python and SQL skills.
• Solid knowledge of the software development lifecycle, testing, documentation through RFCs, and continuous deployment for data systems.
• A genuine interest in keeping up with modern data standards, tools and practices.
• Professional-level English.

Conditions

Full-time senior role based in Madrid, with a hybrid schedule of 4 days in the office and 1 day from home.

Equal opportunity: the company welcomes applicants from all backgrounds.

Benefits

• A personalised 30/60/90-day onboarding plan with a 1:1 mentor from the experienced team.
• Direct influence on platform architecture, data governance and core business decisions.
• A supportive culture that encourages data modeling reviews, knowledge sharing and good practice.