Data Engineer - QuantumBlack, AI by McKinsey
McKinsey & Company
Software Engineering, Data Science
São Paulo, SP, Brazil
Posted on Dec 17, 2025
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Data Engineer - QuantumBlack, AI by McKinsey
Job ID: 104049
Do you want to work on complex and pressing challenges—the kind that bring together curious, ambitious, and determined leaders who strive to become better every day? If this sounds like you, you’ve come to the right place.
Your Impact
You will be part of interdisciplinary teams of data scientists, engineers, designers, and business experts to help solve complex and impactful challenges using data. As a Data Engineer, you will be responsible for designing and building the data foundations that power our analytical solutions.
You will work closely with clients and internal teams to understand data requirements, extract information from diverse sources, build robust pipelines, and ensure data is accessible, reliable, and production ready. Your work will enable our data science teams to build impactful models and insights, supporting high-stakes decisions in industries such as healthcare, energy, retail, and elite sports.
You will apply cutting-edge technologies and collaborate in the development of scalable data products across the full lifecycle of our projects.
You will be based in our São Paulo office as part of the QuantumBlack team.
You’ll gain hands-on experience in building data products across a wide range of industries, supported by experts from QuantumBlack and McKinsey.
You will learn how to approach real-world problems with practical solutions, collaborating with data scientists and other specialists to deliver robust, scalable, and innovative data pipelines. You’ll have access to our internal learning platforms, technical mentorship, and global community, and will have the chance to contribute to internal R&D initiatives and open-source tools like Kedro.
Please submit your CV in English
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'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 qualifications and skills
- Bachelor’s or master’s degree in computer science, engineering, or a related field
- 2+ years of experience in data engineering or backend software development
- Proficiency in Python, Scala, or Java
- Experience designing and building data pipelines using tools such as Pandas, PySpark, Kedro, Airflow, and others
- Solid knowledge of relational databases and experience working with diverse data sources (e.g. APIs, data warehouses, streaming data, unstructured data)
- Interest in applying modern data technologies to solve real-world business problems in cross-functional teams
- Strong communication skills to explain complex technical concepts to both technical and non-technical audiences
- Ability to communicate ideas most effectively - both verbally and in writing - in English and Portuguese/Spanish
Please review the additional requirements regarding essential job functions of McKinsey colleagues.
Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.
FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.
FOR NON-U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.
FOR BRAZILIAN APPLICANTS: Applicants for job positions in any office in Brazil have flexibility regarding qualifications and McKinsey & Company will not require previous experience of more than 6 months. If the job description indicates preferred prior work experience of more than 6 months, applicants for such job position in the Brazilian offices must interpret the preferred qualification described as limited up to 6 months maximum.
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Job Skill Code - DADE - Data Engineer I
Function - Technology
Industry - High Tech
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