> Markdown version of [/jobs/ext/4112015-data-engineer-quantumblack-ai-by-mckinsey](https://www.wearedevelopers.com/jobs/ext/4112015-data-engineer-quantumblack-ai-by-mckinsey). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer - QuantumBlack, AI by McKinsey

- **Company:** McKinsey & Company
- **Location:** Paris, France
- **Contract:** Internship / Graduate position
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, BigQuery, Cloud Computing, Continuous Integration, Information Engineering, Data Security, Cursor, DevOps, Python (Programming Language), PostgreSQL, Machine Learning, Software Tools, Standard Sql, Software Organization, Google Cloud, LangChain, Claude Code, Snowflake, Apache Spark, Generative AI, AI Coding Agents, Agentic-AI, Git, Pandas, Information Technology, Data Management, Machine Learning Operations, Software Version Control, Data Pipelines, Databricks, Programming Languages
- **Published:** October 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fe548b9bf7a42beb

## About the Role

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., * 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
 * Language fluency skills, both verbal and written, in English and French

## Description

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 our Paris office 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.