Data Engineer II – QuantumBlack, AI by McKinsey

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\u2019ll 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.

As a Data Engineer II, you will design scalable data pipelines, manage secure data environments, and prepare data for advanced analytics while collaborating with clients and cross-functional teams. You’ll solve impactful business challenges, contribute to innovative AI projects, and grow as a technologist alongside diverse experts across industries.

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

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

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

You will be in 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. Working with inspiring, multidisciplinary teams, you’ll gain a holistic understanding of AI while collaborating with some of the best technical and business talent in the world.

• Degree in Computer Science, Engineering, Mathematics, or equivalent experience
• 2–5+ years of professional experience in building and deploying data solutions
• Strong coding skills in Python, Scala, or Java, with the ability to write clean, maintainable, and scalable code
• Proven experience in building and maintaining production-grade data pipelines for advanced analytics use cases
• Experience working with structured, semi-structured, and unstructured data
• Hands-on expertise in containerization and orchestration using Docker and Kubernetes for scalable production systems
• Familiarity with distributed computing frameworks (e.g., Spark, Dask), cloud platforms (e.g., AWS, Azure, GCP), and analytics libraries (e.g., pandas, numpy, matplotlib)
• Exposure to DevOps, DataOps, and MLOps concepts and best practices
• Experience with core technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker, Kubernetes, and cloud services (AWS/GCP/Azure)
• Experience with Generative AI (GenAI) or agentic systems is a strong plus
• Prior client-facing or senior stakeholder management experience is beneficial
• Excellent time management and communication skills (verbal and written), with flexibility to adapt across audiences; willingness to travel as needed