Overview
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You will build and operate data pipelines supporting reports, analytics, and machine learning, ensuring quality and forward viability. You’ll raise the bar for development and deployment standards while optimizing performance and scalability. You’ll safeguard data quality, monitor infrastructure, and implement security and privacy controls. You’ll collaborate in cross-functional, agile teams to translate data needs into reliable solutions that drive decision making and product value.
Responsabilidades
Develop and operate data pipelines for reports, analytics, and ML with quality and future viability
Apply software development practices to set new standards for development and deployment
Optimize performance and scalability of data engineering solutions
Ensure data quality and consistency via validation and cleansing




Monitor and troubleshoot data infrastructure to minimize downtime
Implement data security and privacy measures
Collaborate in interdisciplinary agile teams with data scientists, data engineers, product owners and other departments
Requisitos principales
Completed degree in computer science
Strong interest in data engineering and software development
Experience in cloud, containerization and big data; ideally xqbhyrx MS Azure, Kubernetes and Spark
Experience with SQL
Experience developing data pipelines (batch and streaming)
Proficiency in at least one programming language (Python, Scala, Java)
Knowledge of software development lifecycle and best practices (CI/CD, DevOps, testing)
Analytical, agile mindset, independent and hands-on
analytical thinking
agile mindset
independence
MS Azure
Kubernetes
Spark

📌 Data & AI Software Engineer (m/f/d) (Barcelona)
🏢 Schwarz Gruppe
📍 Barcelona