Data Technologies, Analytics & BI Solutions team is responsible for designing, building, and operating scalable Data, AI, and Cloud platforms, enabling reliable, reusable, and business-driven solutions at scale. Working in a tech-driven environment, the team partners with internal IT functions (e.Innovation & AI Forge) to transform validated initiatives into robust, scalable, and production-ready products.
Design and develop cloud-native data pipelines for analytics, AI, and data-driven applications
Build and optimize batch and streaming data ingestion into modern data lakehouse architectures
Ensure data quality, reliability, observability, and governance by design
Support AI/ML workflows by developing feature stores, preprocessing pipelines, and training datasets
Contribute to GenAI and advanced AI use cases through optimized data architectures
Develop backend data services and APIs for production environments
Collaborate with Data Scientists and AI Engineers to industrialize models using MLOps and CI/CD practices
Work with Platform Engineering and SRE teams to ensure scalability,

monitoring, and cost optimization
Contribute to the evolution of the cloud data platform architecture
Ensure security, privacy, and compliance (especially for financial data)
Stay up to date on emerging trends (GenAI, real-time analytics, data mesh, AI platforms)
3 years of experience in Data Engineering or ML Engineering
~ Programming skills (Python, SQL, or Scala; experience with PySparkis a plus)
~ Experience with cloud platforms (AWS, Azure, or GCP) and data storage technologies
~ Hands‑on experience with distributed frameworks (e.Spark)
~ Knowledge of data modeling and data governance concepts
~ Experience with MLOps tools (e.MLflow, Kubeflow, SageMaker)
~ Bachelor’s degree in Computer Science, Engineering, or a related field

What we offer The role is offered within the 3^Area Qualificato category, under the National Collective Labour Agreement for the Banking Sector (CCNL Credito

Data Engineer

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