Designing, developing and optimizing large-scale data pipelines using Apache Spark and Scala.
Building and maintaining batch and near-real-time data processing solutions for high-volume data environments.
Creating reliable, reusable and well-structured datasets consumed by Analytics, Data Science, Machine Learning and business teams.
Working with cloud data platforms (AWS), to process, transform, store and expose data efficiently.
Implementing data quality, validation, monitoring and documentation practices across data pipelines.
Collaborating with Data Engineering, Data Science, Machine Learning, Architecture and business teams to understand requirements and deliver practical data solutions.
Contributing to engineering best practices around code quality, testing, version control, CI/CD and automation.
WHAT YOU’LL BRING
Professional Experience
5+ years of experience in Data Engineering, Big Data Engineering, or similar technical roles. Required
Experience building production-grade data pipelines in large-scale or complex data environments. Required
5+ years of hands-on experience working with Spark in real projects with Scala. Required
Experience working with cloud data platforms. Required
Experience in banking, fintech or regulated environments. Preferred
Language
Fluent Spanish. Preferred
Professional English. Required
Hard Skills
Strong experience with Spark-based distributed processing. Required
Strong Scala coding skills for data engineering use cases. Required
Solid SQL knowledge and experience working with relational and analytical databases. Required
Experience designing and optimizing ETL/ELT processes. Required
Experience with AWS or similar cloud ecosystems; ideally S3, Glue, Athena, EMR, Redshift, IAM or Lake Formation. Required
Experience with Git and collaborative software development practices. Required
Understanding of data quality, validation, monitoring and performance optimization. Required
Experience with CI/CD or DevOps tools such as Jenkins, Sonar, Nexus, Jira, Splunk or similar. Preferred
Experience with Apache Flink, Spark Streaming or near-real-time applications. Preferred
Experience with Apache Iceberg, Delta Lake or modern lakehouse formats. Preferred
Experience with Airflow or workflow orchestration tools. Preferred
Soft Skills
Strong problem-solving skills and ability to work autonomously. Required
Ownership mindset and focus on building reliable, maintainable solutions. Required
Ability to communicate clearly with technical and non-technical stakeholders. Required
Collaborative approach and ability to work across Data Engineering, Data Science, ML and business teams. Required
Curiosity and willingness to learn new tools, frameworks and cloud services. Required
WHAT TO DO NEXT
If this sounds like a role you are interested in, then please apply.
READY TO TAKE THE NEXT STEP IN YOUR JOURNEY?
Open Digital Services is an equal opportunity employer. All applicants will be considered as equal without paying attention to gender identity, sexual orientation, ethnicity, religion, age, political orientation, union membership nor disability status.
We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify, and build.
The personal data you provide as well as any data generated during the selection process are confidential and will be processed by Open Digital Services, S.L. with registered office at Plaza de Santa Bárbara 2, 28004 (Madrid), Madrid, Spain for the sole purpose of managing your participation in the selection processes and, where appropriate, to formalise your recruitment.
For further information about your rights and data protection, please read the Open Digital Services Privacy Policy applicable to this type of data processing here
