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Santander

Global retail and commercial banking group

Senior Data Engineer - ODS

Data EngineeringConfirmed live in the last 24 hours
Full-timeMadrid, SpainNo salary listedIn-person

About the Job

Requirements

  • At least 5 years of experience in Data Engineering, Big Data Engineering, or similar technical roles.
  • Experience building production-grade data pipelines in large-scale or complex data environments.
  • At least 5 years of hands-on experience working with Spark in real projects using Scala.
  • Experience working with cloud data platforms.
  • Strong experience with Spark-based distributed processing.
  • Strong Scala coding skills for data engineering use cases.
  • Solid SQL knowledge and experience working with relational and analytical databases.
  • Experience designing and optimizing ETL/ELT processes.
  • Experience with AWS or similar cloud ecosystems, including services such as S3, Glue, Athena, EMR, Redshift, IAM, or Lake Formation.
  • Experience with Git and collaborative software development practices.
  • Understanding of data quality, validation, monitoring, and performance optimization.
  • Strong problem-solving skills and ability to work autonomously.
  • Ownership mindset and focus on building reliable, maintainable solutions.
  • Ability to communicate clearly with technical and non-technical stakeholders.
  • Collaborative approach and ability to work across Data Engineering, Data Science, Machine Learning, and business teams.
  • Curiosity and willingness to learn new tools, frameworks, and cloud services.
  • Professional English.

Responsibilities

  • Design, develop, and optimize large-scale data pipelines using Apache Spark and Scala.
  • Build and maintain batch and near-real-time data processing solutions for high-volume data environments.
  • Create reliable, reusable, and well-structured datasets consumed by Analytics, Data Science, Machine Learning, and business teams.
  • Work with cloud data platforms to process, transform, store, and expose data efficiently.
  • Implement data quality, validation, monitoring, and documentation practices across data pipelines.
  • Collaborate with Data Engineering, Data Science, Machine Learning, Architecture, and business teams to understand requirements and deliver practical data solutions.
  • Contribute to engineering best practices around code quality, testing, version control, continuous integration and continuous delivery, and automation.

Desired Qualifications

  • Experience in banking, fintech, or regulated environments.
  • Fluent Spanish.
  • Experience with continuous integration and continuous delivery or DevOps tools such as Jenkins, Sonar, Nexus, Jira, Splunk, or similar.
  • Experience with Apache Flink, Spark Streaming, or near-real-time applications.
  • Experience with Apache Iceberg, Delta Lake, or modern lakehouse formats.
  • Experience with Airflow or workflow orchestration tools.

About the Company

Santander

Global retail and commercial banking group

Santander is a global bank focusing on retail and commercial banking in Europe and the Americas, serving individuals and SMEs with regional franchises and a broad consumer finance arm, plus a Corporate & Investment Banking division for multinational clients. It uses its Gravity cloud platform to migrate core banking and rapidly deploy digital services such as Openbank across markets, combining fintech-style agility with a bank's balance sheet. The bank differentiates itself by marrying a large retail footprint with global CIB capabilities under the One Santander verticals model to boost efficiency and cross-border revenue. Its goals include improving returns on tangible equity and financing the green economy through sustainable finance and renewable energy projects.

Company size
10,001+
Company stage
IPO
Headquarters
Boadilla del Monte, Spain
Founded
1902

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