Data Engineer - QuantumBlack, AI by McKinsey

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.

• competitive salary
• comprehensive benefits package
• continuous learning and apprenticeship culture
• mentorship and coaching
• 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
• Ability to work autonomously in a complex environment

• Strong communication
• Time management
• Adaptability
• Python
• SQL
• Databricks