Data Engineer - AI & Data Products

05 ago - Lombardia
Experteer Italy

Experteer Overview

In this role you will design and scale cloud‑native data pipelines and AI‑ready data platforms that enable analytics, AI use cases, and digital applications. You’ll work with cross‑functional teams to ensure data quality, observability, and compliant data handling for production‑grade solutions. You’ll partner with AI engineers to industrialize models and build scalable data services, contributing to a robust cloud data platform backbone. This is a hands‑on, impact‑focused opportunity in a financially regulated, data‑driven environment.

Retribuzione / Benefits

- Design, build and evolve scalable cloud‑native data pipelines for analytics, AI, and data products
- Develop batch and streaming data ingestion to feed modern data lakehouse architectures
- Implement data quality, observability, and governance to ensure trust and compliance by design
- Enable AI/ML workflows by designing feature stores, automating preprocessing, and managing training/inference data
- Build backend data services and APIs to support AI‑powered applications in production
- Collaborate with AI Engineers and Data Scientists to industrialize models through MLOps, CI/CD and scalable deployment




- Coordinate with Platform Engineering and SRE teams to ensure reliable deployment, monitoring, scalability and cost optimization
- Contribute to evolving Cloud Data Platform architecture, optimizing storage, compute, and processing frameworks
- Provide guidance on GenAI integration, real‑time analytics, data mesh concepts, and scalable AI platforms
- Coordinate with internal and external partners to deliver complex data, AI, and digital initiatives

Responsabilità

- 3+ years of experience in Data Engineering or Machine Learning Engineering
- Strong Python (Pandas, PySpark), SQL or Scala for data manipulation
- Experience with cloud platforms (AWS, Azure, or Google Cloud) and data storage tech (Redshift, DynamoDB, BigQuery)
- Hands‑on experience with distributed computing frameworks (Spark, Ray)
- Solid understanding of data modeling, data contracts, and governance
- Experience with MLOps and AI lifecycle tools (MLflow, Kubeflow, Vertex AI, SageMaker)
- Bachelor’s degree in Computer Science, Engineering, or related field

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