Data Engineer I - QuantumBlack, AI by McKinsey

Who You'll Work With

Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.

In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

When you join us, you will have:

Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.

A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.

Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.

World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

Your Impact

As a Data Engineer I, you will design and maintain scalable data pipelines, manage secure data environments, and prepare data for advanced analytics while collaborating with cross-functional teams and clients.

You’ll tackle real-world challenges, contribute to innovative AI solutions, and grow as a technologist by working alongside diverse experts across industries.

In this role, you will design and build scalable, reproducible data pipelines for machine learning. You’ll assess data landscapes, ensure data quality, and prepare data for advanced analytics models. Additionally, you’ll manage secure data environments and contribute to R\&D projects and internal asset development, expanding your technical expertise.

Your work will address real-world challenges across industries. Collaborating with McKinsey’s QuantumBlack and Labs teams, you’ll help build innovative machine learning systems that accelerate AI adoption and solve business problems at scale, enabling clients to achieve meaningful impact.

You’ll be based in London as part of our global Data Engineering community. Working in cross-functional Agile teams, you’ll collaborate with Data Scientists, Machine Learning Engineers, and industry experts to deliver advanced analytics solutions. You’ll be partnering with clients—from data owners to C-level executives—and you’ll help solve complex problems that drive business value.

This role offers an exceptional environment to grow as a technologist and collaborator. You’ll develop expertise at the intersection of technology and business by tackling diverse challenges. Surrounded by inspiring, multidisciplinary teams, you’ll gain a holistic understanding of AI while working with some of the best talent in the world.

Your Qualifications and Skills

Degree in Computer Science, Engineering, Mathematics, or equivalent experience

Upto 2 years’ experience building data pipelines in a professional setting (e.g., internship) is a plus

Ability to write clean, maintainable, scalable, and robust code in Python

Familiarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP)

Basic understanding or exposure to containerization technologies such as Docker and Kubernetes would be beneficial

Exposure to software engineering concepts and best practices, including DevOps, DataOps, and MLOps, will be advantageous

While we advocate using the right tech for the right task, we often leverage: Python, PySpark, the PyData stack, SQL, Airflow, Databricks, Kedro (our open-source data pipelining framework), Dask/RAPIDS, Docker, Kubernetes, and cloud solutions such as AWS, GCP, and Azure

Experience with Generative AI (GenAI) and agentic systems would be considered a strong plus

Excellent time management and organizational skills to succeed in a complex, largely autonomous work environment

Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adapt to different audiences and seniority levels

Willingness to travel