Data Engineer - QuantumBlack, AI by McKinsey

QuantumBlack, AI by McKinsey; Zürich; On-site; CHF 90,000 - 120,000; Full time

Benefits offered by this job

World-class benefits

Job summary

QuantumBlack, AI by McKinsey is seeking a Data Engineer based in Zurich to design and maintain scalable data pipelines for advanced analytics. You will collaborate with cross‑functional teams, manage secure data environments, and prepare data for ML models, contributing to AI projects across industries.

You will work with Data Scientists, ML Engineers, and business leaders to deliver high‑impact analytics solutions, while growing as a technologist in a global community located in Zurich.

Qualifications

• Degree in Computer Science, Engineering, Mathematics, or equivalent experience.
• Up to 2 years of experience building data pipelines (internship acceptable).
• Ability to write clean, maintainable code in Python, Scala or Java.
• Familiarity with analytics libraries, distributed computing (Spark, Dask), and cloud platforms (AWS, Azure, GCP).
• Exposure to DevOps, DataOps and MLOps beneficial.
• Proficiency with Python, PySpark, PyData stack, SQL, Airflow, Databricks, Kedro, Dask/RAPIDS, Docker, Kubernetes, and cloud solutions.
• Practical experience in generative AI application development.
• Proven advisory and leadership experience.
• Proficient communication in German and English.

Responsibilities

• Design and maintain scalable data pipelines for analytics and ML.
• Collaborate with cross-functional teams and clients on data needs.
• Manage secure data environments and prepare data for advanced analytics.
• Contribute to R&D projects and internal asset development.
• Work with McKinsey's QuantumBlack and Labs teams on AI solutions.
• Collaborate in cross-functional Agile teams with data scientists and ML engineers.

Skills

Python

Scala/Java

Pandas/Numpy

Spark/Dask

AWS

Azure

GCP

SQL

Docker/Kubernetes

DevOps

MLOps

Kedro

Databricks

Generative AI

German/English

Education

Bachelor's degree in CS/Engineering/Math

Tools

Databricks

Kedro

Airflow

PySpark

Docker

Kubernetes

PyData stack

Job description

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, 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, 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 Zurich 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 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 of experience building data pipelines in a professional setting (for example, internship) to solve business problems.
• Ability to write clean and maintainable code in an object‑oriented language, e.g., Python, Scala, Java.
• Familiarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP).
• Exposure to software engineering concepts and best practices, inc. DevOps, DataOps and MLOps will be beneficial.
• While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Airflow, Databricks, our own open‑source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more.
• Practical experience in generative AI application development.
• Proven record of advisory works.
• Proven record of leadership in a work setting and/or through extracurricular activities.
• Proficient communication skills in German and English.
• Effective communication and presentation skills, particularly the ability to explain complex technical concepts in a comprehensible manner adapted to different groups of non‑technical audiences e.g. business managers, heads of products, sales & marketing leads.