Data Engineer - QuantumBlack, AI by McKinsey
Summary
Build foundational data infrastructure and scalable pipelines powering AI/ML systems at QuantumBlack, McKinsey's AI arm, working with data scientists and clients on production-ready solutions and generative AI R&D. Core stack: Python, SQL, Databricks/Snowflake/BigQuery, Spark/dbt, MLOps tooling, and AWS/Azure/GCP.
In this role, you will build foundational data infrastructure for AI applications and scalable data pipelines that power advanced AI systems. You’ll work with cross-functional teams and clients to translate hypotheses into engineered data solutions, ensuring secure environments and production-readiness. You’ll contribute to R&D efforts in agentic and Generative AI, accelerating client value and AI adoption. This is a high-impact, growth-focused role in a collaborative, high-performance culture.
Pay / Benefits- competitive salary
- comprehensive benefits package
- world-class learning and apprenticeship culture
- Design and maintain scalable data pipelines for AI systems
- Build robust data foundations and secure data environments
- Prepare data for AI-driven solutions and model deployment
- Collaborate with Data Scientists, ML Engineers, and clients in cross-functional teams
- Contribute to R&D initiatives for next-generation AI capabilities
- Support clients from data owners to executives to drive business value
- Participate in Agile teams and deliver production-ready data components
- Translate hypotheses into data features and manage data quality fundamentals
- Degree in Computer Science/Engineering, or equivalent experience
- 1+ years of relevant professional data engineering experience
- Strong Python and SQL for data engineering and production-grade coding
- Experience building end-to-end data pipelines for AI/ML or BI, including embeddings generation and vector search
- Proficiency with data platforms (Databricks, Snowflake, BigQuery, PostgreSQL) and data engineering tools (Pandas, Spark, dbt)
- Hands-on MLOps/LLMOps knowledge (CI/CD for data workflows, LangSmith/Langfuse, Terraform)
- Cloud platform experience (AWS, Azure, GCP)
- Strong communication skills in English and local language(s)
- Experience with coding agents (Cursor, Claude Code, Codex) is a plus
- Excellent time management in autonomous work environments
- Strong communication
- Client-facing collaboration
- Adaptability and resilience
- Python
- SQL
- Data pipelines
Skills
- Agentic AI
- Agile
- AI
- Ai Enablement
- AWS
- Azure
- BigQuery
- CI/CD
- Claude Code
- Cloud
- Data Engineering
- Data Pipelines
- Data Quality
- Databricks
- dbt
- Embeddings
- GCP
- Generative AI
- Langfuse
- LangSmith
- LLMOps
- Machine Learning
- MLOps
- Model Deployment
- pandas
- PostgreSQL
- Python
- Snowflake
- Spark
- SQL
- Terraform
- Vector Search