Data Engineer I

Role overview

QuantumBlack, AI by McKinsey is looking for a Data Engineer I to join its London team and help build the data foundations behind advanced AI solutions. The role sits within a high-performance environment where curiosity, resilience, and a willingness to keep improving are valued. You will work on the infrastructure that supports LLM-based applications, retrieval systems, workflows, and emerging agentic architectures.

What you'll do

In this position, you will design and maintain scalable data pipelines, manage secure data environments, and prepare data for AI-led products. You will work closely with cross-functional colleagues and clients to turn business problems into reliable data components that can support machine learning, autonomous systems, and production-ready AI use cases.

Your work will also include assessing data landscapes, applying data quality practices, translating simple ideas into engineered features, and contributing to research and development efforts that expand next-generation AI capabilities. You will collaborate across QuantumBlack, AI by McKinsey and QuantumBlack Labs, supporting the creation of robust enterprise AI solutions with measurable business impact.

Team and working environment

You will be based in London and part of a global data engineering community. The job involves agile, cross-functional teamwork with data scientists, machine learning engineers, and industry specialists. You will also interact with clients ranging from data owners to senior executives, helping solve complex problems while developing your capability as a client-facing technologist.

Growth and culture

The company offers a learning-heavy environment with coaching, apprenticeship, and ongoing feedback. You are expected to contribute ideas, work with integrity, and thrive in a fast-moving setting. The team is international, spanning more than 65 countries and over 100 nationalities, and the organisation emphasizes continuous development and broad exposure.

Qualifications and technical background

Applicants should have a degree in Computer Science, Engineering, or an equivalent background. Prior exposure to data work, including internships or academic projects, is important. Strong coding ability is required, especially in Python and SQL, along with experience writing clear, well-structured documentation.

Useful familiarity includes data engineering for Agentic AI, Generative AI, Machine Learning, or Business Intelligence; working with structured and unstructured data; and handling both streaming and batch processing. Experience with platforms and tools such as Databricks, Snowflake, BigQuery, PostgreSQL, AWS, Azure, GCP, Pandas, Spark, dbt, and LangChain is valuable. Knowledge of Git, DevOps basics, CI/CD, and MLOps or LLMOps concepts is also expected. Experience with coding assistants such as Cursor, Claude Code, or Codex would be an advantage.

Additional qualities

Strong time management, the ability to work independently, quick learning, adaptability across different project environments and technology stacks, and excellent written and spoken English are all important for success in this role.

Benefits and rewards

You will receive apprenticeship, mentorship, and exposure designed to accelerate your development. The role also comes with a competitive salary based on location, experience, and skills, along with a comprehensive benefits package supporting your well-being and that of your family.