Data Engineering Consultant - QuantumBlack, AI by McKinsey (m/f/d) - Consulting, Datenbankentwicklun

What you'll do 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 McKinsey’s 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 Germany 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. You will 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 leading AI and data experts in the industry. Your background Degree in Computer Science/Engineering, or equivalent experience 2+ years of relevant professional experience building and deploying data solutions Strong proficiency in Python and SQL for data engineering and experience writing robust, production-grade code, including deploying code across environments Proven experience building end-to-end data pipelines and platforms for Agentic AI, Generative AI, Machine Learning, or Business Intelligence, covering data preparation, embeddings generation, vector search, and system integration using modern frameworks (Spark, dbt, LangChain) A strong foundation in system design, data storage, and reliability with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.) and data engineering tools (e.g., Pandas, Spark, dbt, etc.) Hands-on experience with MLOps/LLMOps principles, including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform) Experience building systems with different data formats (structured vs unstructured) and data processing methods (streaming vs batch) and deploying across major cloud platforms (AWS, Azure, GCP) Exceptional time management in a complex and largely autonomous work environment Commercial client-facing or senior stakeholder management experience is beneficial Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus Strong communication skills, both verbal and written, in German and English