Data Engineer - QuantumBlack, AI by McKinsey

McKinsey; Amsterdam; Híbrido; EUR 70 000 - 110 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary

Comprehensive benefits

Global community

BeNeLux office locations

Career growth opportunities

Resumo da oferta

McKinsey is seeking a data engineering professional to build scalable data foundations for AI-driven systems. You will design data pipelines, secure environments, and collaborate with data scientists and engineers across industries to scale next-generation AI capabilities.

You will work with BeNeLux offices and global Data Engineering teams, applying modern data platforms and cloud ingestions, while contributing to R&D for agentic AI solutions and enterprise-scale deployments.

Qualificações

• Degree in Computer Science/Engineering, or equivalent experience.
• Experience in a data-focused role (internships, academic projects).
• Ability to write clean, well-documented code in Python and SQL.
• Interest in data engineering for Agentic/Generative AI and BI across data formats.
• Familiarity with data platforms (Databricks, Snowflake, BigQuery, SQL) and cloud (AWS/Azure/GCP).
• Exposure to DevOps/MLOps/CI/CD practices and Git.
• Strong time management in autonomous environments.
• Willingness to learn quickly and adapt to different tech stacks.
• Experience with coding agents (Cursor, Claude Code, Codex) is a plus.
• Strong communication in English.

Responsabilidades

• Build scalable data pipelines and foundational data infrastructure for AI apps.
• Design and maintain secure data environments for AI systems.
• Collaborate with data scientists and engineers across industries.
• Translate hypotheses into engineered features for models and solutions.
• Contribute to R&D for agentic AI capabilities and scalable enterprise solutions.

Conhecimentos

Python

SQL

Data engineering

Databricks

Snowflake

BigQuery

AWS

Azure

GCP

Pandas

Spark

dbt

LangChain

Git

Formação académica

Degree in Computer Science/Engineering

Ferramentas

Databricks

Snowflake

BigQuery

dbt

LangChain

Spark

Pandas

Git

CI/CD

MLOps

LLMOps

Cursor

Claude Code

Descrição da oferta de emprego

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.

YOUR IMPACT

You will build the foundational data infrastructure that powers cutting-edge AI applications leveraging LLMs, retrieval systems, workflows, and emerging agentic architectures. You will design and maintain scalable data pipelines, manage secure data environments, and prepare data for AI-driven systems while collaborating with cross-functional teams and clients. You’ll tackle real-world challenges by contributing to the development of next-generation AI systems and grow as a technologist by working alongside diverse experts across industries. You will design and build the scalable, reproducible data components essential for machine learning, agentic, and autonomous AI systems. You’ll assess data landscapes, apply data quality fundamentals, and prepare data for AI solutions. Additionally, you’ll learn to translate simple hypotheses into engineered features, manage secure data environments, and contribute to R&D initiatives focused on innovating and scaling next-generation AI capabilities. Your work will help solve some of the most complex and high-impact challenges facing clients across industries. Collaborating across QuantumBlack, AI by McKinsey and QuantumBlack Labs teams, you’ll help develop innovative AI capabilities and scalable enterprise solutions. You’ll help build robust data foundations for scalable, production-ready AI systems. Your contributions will directly support the firm’s ability to accelerate AI adoption, solve complex business problems at scale, and enable clients to achieve meaningful, lasting impact. You’ll be based in one of our BeNeLux offices as part of our global Data Engineering community. Working in cross-functional Agile teams, you’ll collaborate closely with Data Scientists, Machine Learning Engineers, and industry experts to deliver AI solutions. By partnering with clients from data owners to C-level executives you’ll help solve complex problems that drive tangible business value and begin to build your skills as a client-facing technologist. Your work offers a unique opportunity to grow at the forefront of AI, data engineering, and emerging agentic technologies. You’ll develop expertise at the intersection of technology and business by tackling diverse challenges in the evolving AI landscape. Working alongside multidisciplinary teams, you’ll gain a holistic understanding of how data engineering enables advanced AI while collaborating with several leading AI and data experts in the industry.

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

• Degree in Computer Science/Engineering, or equivalent experience
• Experience in a data-focused role (internships, academic projects)
• Ability to write clean, well-documented code in a modern programming language, with a strong preference for Python and SQL
• Interest in or exposure to data engineering in the context of Agentic AI, Generative AI, Machine Learning, or Business Intelligence across different types of data formats (structured vs unstructured) and processing methods (streaming vs batch)
• Familiarity with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.), cloud platforms (AWS, Azure, GCP) and engineering tools (Pandas, Spark, dbt, LangChain, etc.)
• Exposure to modern software development practices, including version control (Git) and foundational concepts in DevOps and MLOps/LLMOps and CI/CD principles
• Exceptional time management in a complex and largely autonomous work environment
• Willingness to learn quickly and adapt to different project situations and tech stacks
• Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus
• Strong communication skills, both verbal and written, in English

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.