Data Software Engineer
Build and maintain the data platform that powers high-volume gaming services, using Java/Python, Kafka, Spark/Flink, and DevOps practices to ensure reliable ingestion, transformation, and data quality.
- Compensation
- Not disclosed
- Location
- Madrid, Spain
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Nice to have
- Experience defining and monitoring data-quality standards, metrics and KPIs.
- Experience with Kubernetes, Docker and Argo CD.
- Knowledge of Apache Iceberg.
- Knowledge of Exasol.
- Experience with scripting languages such as Shell.
- Experience with the Confluent Platform.
- Experience building platform or “as-a-service” capabilities for other engineering teams.
Full description
We build game-changing products and scalable platforms for complex, high-volume digital markets.
Our cross-functional teams create online platforms and software solutions that reach hundreds of thousands of users every day.
Your mission
Are you ready to push technology into the future as a Data Software Engineer at The Workshop?
We’re looking for skilled, versatile and collaborative engineers with excellent design and problem-solving abilities. If you have experience developing high-performance applications and are ready to tackle challenges across the stack, we want to hear from you.
In this role, you’ll apply strong software-engineering fundamentals to building the services and capabilities of our data platform. You’ll design and develop systems that orchestrate, configure and expose ingestion, transformation and data-quality capabilities as a service, following a complete DevOps approach.
We’re looking for someone comfortable building production software: delivering new functionality while ensuring that everything built is reliable, observable, maintainable and easy to support.
What you’ll do
- Build services that orchestrate and expose ingestion, transformation and data-quality capabilities to other teams.
- Develop ingestion and connector-based integration capabilities using Kafka and Kafka Connect.
- Integrate and orchestrate distributed processing engines such as Apache Spark, Flink or Beam behind clean service APIs.
- Abstract the underlying execution of data-processing technologies.
- Implement comprehensive monitoring and alerting to track service health, data quality and resource utilisation.
- Investigate and support production issues, improving reliability and reducing recurring operational problems.
- Support performance-tuning initiatives and identify opportunities to increase efficiency and throughput.
- Use approved AI-assisted engineering tools responsibly for development, testing, documentation and troubleshooting.
- Direct AI coding agents as part of everyday delivery by providing clear context, critically reviewing their output and taking responsibility for the quality, security and design of everything that ships.
- Work with engineers and product owners using agile methodologies.
- Take end-to-end ownership of your work under a DevOps philosophy covering the entire software development lifecycle.
- Follow best practices in design, coding, testing, operations and monitoring.
- Give and receive constructive feedback through code reviews.
- Collaborate, perform peer reviews, share knowledge and develop skills across the team.