Data Engineer - QuantumBlack, AI by McKinsey

Overview

In this role you will build foundational data infrastructure powering AI applications at scale. You will design scalable data pipelines, manage secure data environments, and prepare data for AI-driven systems in collaboration with cross-functional teams. You will contribute to next-generation AI capabilities and production-ready data components, accelerating AI adoption for clients. You will grow as a technologist within a global, apprenticeship-driven culture that values curiosity and ethics.

Retribuzione / Benefits competitive salary

comprehensive benefits package

continuous learning and apprenticeship culture

mentorship and coaching

global collaboration across 65+ countries

Responsabilità Design and maintain scalable data pipelines for AI systems

Build robust data foundations and secure data environments

Collaborate with Data Scientists, ML Engineers, and clients to translate hypotheses into engineered features

Assess data landscapes and apply data quality fundamentals

Contribute to R&D initiatives for scaling next-gen AI capabilities

Work in cross-functional Agile teams and support client-facing technologist development

Learn and adapt to multiple tech stacks across industries

Requisiti fondamentali Degree in Computer Science/Engineering, or equivalent experience

Experience in data-focused roles (internships, academic projects)

Proficiency in Python and SQL

Familiarity with data platforms (Databricks, Snowflake, BigQuery, PSQL) and cloud platforms (AWS, Azure, GCP)

Exposure to data engineering in Agentic/Generative AI and ML contexts

Understanding of DevOps and MLOps/CI/CD concepts

Strong communication in English

Experience using coding agents (Cursor, Claude Code, Codex) is a plus

Ability to work autonomously in a complex environment

Strong communication

Time management

Adaptability

Python

SQL

Databricks