Data Engineer I - QuantumBlack, AI by McKinsey

QuantumBlack, AI by McKinsey
City of London
3 weeks ago
Create job alert
Data Engineer I - QuantumBlack, AI by McKinsey

Join to apply for the Data Engineer I - QuantumBlack, AI by McKinsey role at 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
  • Up to 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

Seniority Level

Entry level


Employment Type

Full‑time


Job Function

Consulting


Industries

Business Consulting and Services


#J-18808-Ljbffr

Related Jobs

View all jobs

Research Engineer in Chip-Based Quantum Key distribution

Research Engineer in Chip-Based Quantum Key distribution

Systems Engineer: Photonics and Acoustics

Nanophotonics Engineer

Systems Engineer: Photonics and Acoustics

Systems Engineer: Photonics and Acoustics

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Quantum Computing Tools Do You Need to Know to Get a Quantum Computing Job?

Quantum computing is one of the most exciting frontiers in science and technology — and the job market reflects that excitement. But for aspiring practitioners, the sheer number of tools, frameworks, programming languages and hardware platforms can feel overwhelming. One job advert mentions Qiskit, another talks about Cirq or Pennylane. You see references to quantum annealers and superconducting qubits, to measurement hardware and simulators, to noise mitigation libraries and cloud platforms. It’s easy to conclude that unless you master every quantum tool, you’ll never get a job. Here’s the honest truth most quantum computing hiring managers won’t explicitly tell you: 👉 They don’t hire you because you know every tool — they hire you because you can apply the right tools to solve real problems and explain why your solutions work. Tools matter, but context, understanding, judgement and results matter more. So how many quantum computing tools do you actually need to know to succeed in a job search? The real answer is significantly fewer than most people assume — and far more focused by role. This article breaks down what tools really matter in quantum jobs, which ones are core, which are role-specific, and how you can build a coherent toolkit that employers actually value.

What Hiring Managers Look for First in Quantum Computing Job Applications (UK Guide)

Quantum computing is one of the fastest-evolving fields in technology, blending physics, mathematics, computer science and engineering. Roles in this space — from Quantum Algorithm Developer and Quantum Software Engineer to Quantum Research Scientist and Quantum Hardware Specialist — are highly sought after, and hiring managers are exceptionally selective. Because quantum computing is complex and multidisciplinary, recruiters and hiring managers look for clear, concrete evidence of relevant expertise and impact right at the start of your application. They often decide whether to read your CV in detail within the first 10–20 seconds, based on a handful of high-value signals. This guide breaks down exactly what hiring managers look for first in quantum computing applications, how they assess CVs and portfolios, and what you can do to optimise your application to get noticed in the UK quantum job market.

Riverlane Jobs in Quantum Computing

If you’re looking for Riverlane jobs in quantum computing, you’re aiming at one of the most important layers in the quantum stack: quantum error correction (QEC). In simple terms, Riverlane focuses on the software, methods & tooling that help quantum computers produce reliable results despite noise. That matters because as quantum hardware scales, the ability to correct errors becomes the difference between “interesting experiments” and “useful quantum computing”. This guide is written for UK job seekers who want to understand: what Riverlane does (in job-seeker language) the roles they hire for the skills that map best to their work how to tailor your CV & LinkedIn how to prepare for interviews how to find & land Riverlane vacancies in the UK You do not need to be a quantum PhD to have a realistic pathway in. But you do need to understand the problem they’re solving & position your experience around it.