Data Engineer I – QuantumBlack, AI by McKinsey

Overview

Join McKinsey’s data engineering team in London to build scalable data foundations for cutting-edge AI systems. You will partner with cross-functional units to deliver production-ready data pipelines and secure data environments that power enterprise AI. The role blends hands-on engineering with R&D to scale agentic and generative AI capabilities for client impact. You’ll learn rapidly in a high-performance culture and contribute to shaping AI solutions at scale.

Pay / Benefits

• competitive salary
• comprehensive benefits package
• global exposure
• structured learning and apprenticeship culture
• mentorship and career development
• inclusive, diverse workforce

Responsibilities

• Build foundational data infrastructure powering AI applications (LLMs, retrieval systems, workflows)
• Design and maintain scalable data pipelines and secure data environments
• Prepare data for AI-driven systems and collaborate with cross-functional teams
• Develop scalable, reproducible data components for ML, agentic, and autonomous AI
• Assess data landscapes and data quality; translate hypotheses into engineered features
• Contribute to R&D initiatives to innovate and scale AI capabilities
• Collaborate with McKinsey QuantumBlack, AI by McKinsey, and QuantumBlack Labs
• Support client-facing technologist work and cross-functional agile delivery

Key requirements

• Degree in Computer Science/Engineering, or equivalent experience
• Experience in a data-focused role (internships, academic projects)
• Proficiency in Python and SQL
• Exposure to Agentic AI, Generative AI, ML, or BI across data formats and processing methods
• Familiarity with data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.) and cloud platforms (AWS, Azure, GCP)
• Experience with Pandas, Spark, dbt, LangChain, etc.
• Knowledge of Git, DevOps and MLOps/LLMOps concepts, CI/CD
• Strong verbal and written communication in English
• Willingness to learn quickly and adapt to different tech stacks
• Experience with coding agents (Cursor, Claude Code, Codex) is a plus

• Strong communication
• Time management in autonomous environments
• Adaptability and fast learning
• Python
• SQL
• Pandas

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