Data Engineer - QuantumBlack, AI by McKinsey

In this role you design and maintain scalable data pipelines to enable advanced analytics and AI solutions. You will work within cross-functional teams, including McKinsey’s QuantumBlack and Labs, to solve business problems at scale and contribute to R&D and internal asset development. You’ll prepare data for machine learning, ensure data quality, and manage secure data environments. The position offers a strong learning culture, mentorship, and exposure to diverse global teams and clients.

• continuous learning and apprenticeship culture
• mentorship and growth opportunities
• global diverse team and collaboration
• competitive salary based on location and skills
• comprehensive benefits package for well-being
• opportunity to work with leading AI solutions

• Design and maintain scalable data pipelines for machine learning
• Assess data landscapes and ensure data quality for analytics models
• Manage secure data environments and support data governance
• Collaborate with cross-functional teams and clients to deliver analytics solutions
• Contribute to R&D projects and internal asset development
• Partner with clients from data owners to executives to drive business value

• Up to 2 years of experience building data pipelines
• Proficiency in object-oriented languages (Python, Scala, Java)
• Familiarity with analytics libraries (pandas, numpy, matplotlib) and distributed computing (Spark, Dask)
• Experience with cloud platforms (AWS, Azure, GCP) and SQL
• Exposure to DevOps, DataOps, and MLOps beneficial
• Generative AI application development experience
• Proven advisory and leadership experience
• Proficient in German and English
• Ability to explain complex concepts to non-technical audiences

• effective communication
• presentation skills
• leadership
• Python
• PySpark
• PyData stack