Data Engineer I - QuantumBlack, AI by McKinsey

Data Engineer I - QuantumBlack, AI by McKinsey

Full-Time 36000 - 60000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and maintain scalable data pipelines while collaborating with cross-functional teams.
  • Company: Join QuantumBlack, AI by McKinsey, a leader in innovative AI solutions.
  • Benefits: Enjoy competitive salary, comprehensive benefits, and a focus on holistic well-being.
  • Other info: Work with diverse experts in a global community across 65+ countries.
  • Why this job: Make a real impact in AI while growing your skills in a supportive environment.
  • Qualifications: Degree in relevant field and up to 2 years of experience in data engineering.

The predicted salary is between 36000 - 60000 £ per year.

Your Growth

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 will 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 will receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

  • 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, all while upholding our unwavering commitment to ethics and integrity. 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

Data Engineer I - QuantumBlack, AI by McKinsey employer: Mckinsey & Company

As a Portfolio Manager - Events at our firm, you will thrive in a dynamic and high-performance environment that champions continuous learning and diverse perspectives. We offer exceptional benefits and a global community of colleagues, ensuring your contributions are valued and impactful from day one. With structured mentorship and opportunities for professional growth, you'll be empowered to make a real difference while enjoying a collaborative and innovative work culture.

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Contact Details:

Mckinsey & Company Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer I - QuantumBlack, AI by McKinsey

Tip Number 1

Network like a pro! Reach out to current employees at QuantumBlack or similar companies on LinkedIn. Ask them about their experiences and any tips they might have for landing a role. Personal connections can make all the difference!

Tip Number 2

Prepare for those interviews by brushing up on your technical skills. Practice coding challenges and be ready to discuss your past projects. Show them you can not only talk the talk but also walk the walk when it comes to data engineering.

Tip Number 3

Don’t forget to showcase your soft skills! Being a great communicator and collaborator is key in a cross-functional team. Be ready to share examples of how you've worked with others to solve problems or deliver results.

Tip Number 4

Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive and engaged. Make sure to highlight your passion for AI and data engineering in your application!

We think you need these skills to ace Data Engineer I - QuantumBlack, AI by McKinsey

Data Pipeline Development
Python Programming
Analytics Libraries (pandas, numpy, matplotlib)
Distributed Computing Frameworks (Spark, Dask)
Cloud Platforms (AWS, Azure, GCP)
Containerization Technologies (Docker, Kubernetes)
Software Engineering Concepts (DevOps, DataOps, MLOps)

Some tips for your application 🫡

Show Your Passion for Data:When you're writing your application, let your enthusiasm for data engineering shine through! Share specific examples of projects or experiences that sparked your interest in building data pipelines and working with analytics. We love seeing candidates who are genuinely excited about the field.

Tailor Your Application:Make sure to customise your application to highlight how your skills align with the role. Mention your experience with Python, cloud platforms, or any relevant tools like Spark or Docker. This shows us that you understand what we're looking for and that you're a great fit for our team.

Be Clear and Concise:Keep your application straightforward and to the point. Use clear language and avoid jargon unless it's relevant. We appreciate candidates who can communicate complex ideas simply, as this is key in our collaborative environment.

Apply Through Our Website:Don't forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our culture and values while you’re at it!

How to prepare for a job interview at Mckinsey & Company

Know Your Tech Stack

Make sure you’re familiar with the technologies mentioned in the job description, like Python, SQL, and cloud platforms. Brush up on your knowledge of analytics libraries and distributed computing frameworks, as these will likely come up during technical discussions.

Showcase Your Problem-Solving Skills

Prepare to discuss specific examples where you've tackled complex data challenges. Think about how you’ve designed data pipelines or improved data quality in previous projects. This will demonstrate your ability to contribute to real-world solutions.

Emphasise Continuous Learning

Since the role values growth and development, be ready to talk about how you embrace feedback and learn from experiences. Share instances where you’ve taken constructive criticism to improve your skills or processes.

Communicate Effectively

Practice explaining technical concepts in simple terms, as you’ll need to collaborate with cross-functional teams and clients. Highlight your communication skills and adaptability to different audiences, which are crucial for this role.