Data Engineer - QuantumBlack, AI by McKinsey

QuantumBlack, AI by McKinsey is a specialist unit that helps organisations adopt advanced analytics and machine‑learning solutions. As a Data Engineer you will join a team that blends technology with business insight, operating in a fast‑paced, high‑achievement setting where curiosity and resilience are prized. In this position you will create and sustain robust data pipelines that feed machine‑learning models, ensure that data stores remain secure, and ready datasets for sophisticated analytical work. Daily tasks involve evaluating data landscapes, guaranteeing quality, and collaborating with data scientists, ML engineers and industry specialists to deliver end‑to‑end AI systems. You will also contribute to research projects and internal tooling, expanding the technical repertoire of the group. The role requires a university degree in computer science, engineering, mathematics or a comparable background, together with up to two years of hands‑on experience building data pipelines, whether through internships or early‑career roles. Candidates must be comfortable writing clean, object‑oriented code in languages such as Python, Scala or Java, and should know analytics packages like pandas, numpy and matplotlib, as well as distributed frameworks such as Spark or Dask. Familiarity with cloud services (AWS, Azure, GCP) and basic software‑engineering practices is essential, and fluency in both German and English is expected for effective communication. Additional assets include exposure to DevOps, DataOps or MLOps practices, work with tools like PySpark, SQL, Airflow, Databricks, Kedro, Docker and Kubernetes, and experience in generative‑AI projects