Data Engineer - QuantumBlack, AI by McKinsey

McKinsey & Company; Paris; Sur place; EUR 40 000 - 55 000; Plein temps

Résumé du poste

A leading consulting firm in Paris is seeking a Data Engineer to design and maintain scalable data pipelines, collaborate with cross-functional teams, and tackle real-world challenges using advanced analytics and machine learning solutions. Ideal candidates will have a degree in a relevant field and familiarity with tech such as Python and AWS. This role offers a supportive environment for growth.

Prestations

Comprehensive benefits package

Opportunities for continuous learning

Global community exposure

Qualifications

• 0-2+ years of experience building data pipelines in a professional setting.
• Ability to write clean and maintainable code in an object-oriented language.
• Familiarity with analytics libraries and distributed computing frameworks.

Responsabilités

• Design and maintain scalable data pipelines.
• Collaborate with cross-functional teams and clients.
• Manage secure data environments and prepare data for advanced analytics.

Connaissances

Data pipeline building

Python

Data analytics (pandas, numpy)

Strong communication in English and French

Time management

Formation

Degree in Computer Science, Engineering, Mathematics

Outils

AWS

SQL

Docker

Kubernetes

PySpark

Description du poste

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.

What 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.

Role overview

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 Paris 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. Partnering with clients, from data owners to C-level executives, you’ll 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.

Our Tech Stack

We advocate for using the right tech for the right task, and commonly leverage technologies such as Python, PySpark, the PyData stack, SQL, Airflow, Databricks, Kedro, Dask / RAPIDS, Docker and Kubernetes, and cloud platforms including AWS, GCP, and Azure.

Qualifications

• Degree in Computer Science, Engineering, Mathematics, or equivalent experience
• 0-2+ years of experience building data pipelines in a professional setting (e.g., internship) would be considered a plus
• 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
• Strong communication skills, both verbal and written, in English and French, with the ability to adjust your style to suit different perspectives and seniority levels
• Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment.