Data Engineer II - QuantumBlack, AI by McKinsey

About the role

QuantumBlack, AI by McKinsey is looking for a Data Engineer II to work on real-world, high-impact projects across many industries. You will collaborate with the QuantumBlack Labs team to build complex machine learning systems that accelerate AI work and solve business problems at speed and scale. You will work in cross-functional Agile teams with data scientists, machine learning engineers, other data engineers, project managers and industry experts.

Key responsibilities

• Contribute to cross-functional problem-solving sessions with clients, from data owners and users to C-level executives, to build impactful analytics solutions
• Contribute to R&D projects and internal asset development
• Design and build GenAI applications (RAG, agentic AI, etc.) together with data scientists
• Map data fields to hypotheses and curate, wrangle and prepare data for advanced analytics models
• Assess data quality based on the client's data landscape
• Create and manage data environments while maintaining information security standards
• Design and build robust, modular, scalable, deployable, reproducible and versioned data pipelines for machine learning
• Help build and maintain the technical platform for advanced analytics engagements, covering both data science and data engineering
• Work in global, multidisciplinary teams and partner closely with clients

Required profile

• Degree in computer science, engineering, mathematics or equivalent experience
• 2+ years of relevant professional experience
• Proven experience building data pipelines in production for advanced analytics use cases
• Experience working across structured, semi-structured and unstructured data
• Commercial client-facing or senior stakeholder management experience is beneficial

Required skills

• Clean, maintainable, scalable code in an object-oriented language such as Python, Scala or Java
• Exposure to software engineering concepts including DevOps, DataOps and MLOps (a plus)
• Familiarity with distributed computing, cloud platforms, containerization and analytics libraries (pandas, numpy, matplotlib)
• Big Data platforms and tools such as AWS, Azure, GCP, Spark, Kafka, Snowflake, GCS Data Proc, Azure Data Factory, AWS Glue, Apache Beam/Flink, Python/PySpark

What we offer

• A competitive salary based on location, experience and skills
• Structured learning and apprenticeship programmes with coaching and feedback
• A global community of colleagues across 65+ countries and over 100 nationalities
• A comprehensive benefits package for you and your family