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.
- 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.
- Other info: Work in a diverse global community with exceptional colleagues across 65+ countries.
The predicted salary is between 36000 - 60000 ÂŁ 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
Contact Detail:
Mckinsey & Company Recruiting 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 McKinsey on LinkedIn. Ask them about their experiences and any tips they might have for landing the job. Personal connections can make a huge difference!
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can talk confidently about data pipelines, Python coding, and any relevant tools like Spark or Docker. Practice common interview questions and be ready to showcase your problem-solving abilities.
✨Tip Number 3
Show your passion for AI and data engineering! During interviews, share your personal projects or experiences that highlight your curiosity and drive. This will help you stand out as someone who’s genuinely excited about the field.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining our team and contributing to innovative solutions.
We think you need these skills to ace Data Engineer I - QuantumBlack, AI by McKinsey
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 well-structured applications that make it easy for us to see your qualifications and potential contributions right away.
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 problems, especially in data engineering. Think about how you’ve designed data pipelines or managed secure data environments, and be ready to explain your thought process and the impact of your solutions.
✨Emphasise Continuous Learning
Since the role values growth and development, be prepared to talk about how you embrace feedback and learn from experiences. Share instances where you’ve taken input from others to improve your skills or projects, showing that you’re proactive about your professional growth.
✨Communicate Effectively
Strong communication is key, especially when collaborating with cross-functional teams. Practice explaining technical concepts in simple terms, as you may need to adapt your communication style for different audiences, from data owners to C-level executives.