Senior Data Engineer - Spark, AWS & Fintech, Madrid

Banco Santander SA; Madrid; Hybrid; EUR 70,000 - 95,000; Full time

Job summary

Open Digital Services in Madrid seeks a Senior Data Engineer to design and optimize large-scale data pipelines using Spark, primarily with Scala, on AWS cloud. You will build batch and near-real-time data processing solutions, ensuring data quality and governance while collaborating with Data Science, ML and business teams.

The role requires 5+ years in data engineering, strong Spark/PySpark skills, and experience in regulated environments.

Qualifications

• 5+ years of experience in Data Engineering, Big Data Engineering, Software Engineering or similar technical roles.
• Experience building production-grade data pipelines in large-scale or complex data environments.
• Hands-on experience with Apache Spark in real projects, preferably with Scala.
• Experience working with cloud data platforms.
• Experience in banking, fintech or regulated environments.

Responsibilities

• Design, build and optimize large-scale data pipelines using Apache Spark, preferably Scala.
• Create batch and near-real-time data processing solutions for high-volume data environments.
• Develop reliable, reusable datasets for Analytics, Data Science and ML teams.
• Work with cloud data platforms (AWS) to process, transform, store and expose data.
• Implement data quality, validation, monitoring and documentation across pipelines.
• Collaborate with Data Engineering, Data Science, ML and business teams to deliver practical data solutions.
• Contribute to engineering best practices around code quality, testing, version control, CI/CD and automation.

Skills

PySpark

Spark SQL

Python

Scala

SQL

ETL/ELT

Cloud data platforms

Data quality

CI/CD

DevOps practices

GIt

Jenkins

Jira

Spark Streaming

Apache Flink

Iceberg / Delta Lake

Airflow

Tools

AWS

S3

Glue

Athena

EMR

Redshift

IAM

Lake Formation

Git

Jenkins

Airflow

Job description

Open Digital Services in Madrid seeks a Senior Data Engineer to design and optimize large-scale data pipelines using Spark, primarily with Scala, on AWS cloud. You will build batch and near-real-time data processing solutions, ensuring data quality and governance while collaborating with Data Science, ML and business teams.

The role requires 5+ years in data engineering, strong Spark/PySpark skills, and experience in regulated environments.