Overview In this role you will build foundational data infrastructure powering AI applications at scale. You will design scalable data pipelines, manage secure data environments, and prepare data for AI-driven systems in collaboration with cross-functional teams. You will contribute to next-generation AI capabilities and production-ready data components, accelerating AI adoption for clients.

You will grow as a technologist within a global, apprenticeship-driven culture that values curiosity and ethics.

Retribuzione / Benefits comprehensive benefits package continuous learning and apprenticeship culture global collaboration across 65+ countries Design and maintain scalable data pipelines for AI systems Build robust data foundations and secure data environments Collaborate with Data Scientists, ML Engineers,



and clients to translate hypotheses into engineered features Assess data landscapes and apply data quality fundamentals Contribute to R&D; initiatives for scaling next-gen AI capabilities Work in cross-functional Agile teams and support client-facing technologist development Learn and adapt to multiple tech stacks across industries Degree in Computer Science/Engineering, or equivalent experience Experience in data-focused roles (internships, academic projects) Proficiency in Python and SQL Familiarity with data platforms (Databricks, Snowflake, BigQuery, PSQL) and cloud platforms (AWS, Azure, GCP) Exposure to data engineering in Agentic/Generative AI and ML contexts Understanding of DevOps and MLOps/CI/CD concepts Strong communication in English Experience using coding agents (Cursor, Claude Code, Codex) is a plus Python SQL Databricks

📌 Data Engineer - QuantumBlack, AI by McKinsey (Pavia)
🏢 McKinsey u0026
📍 Pavia