AI Data Engineer: Build Scalable AI Data Pipelines

McKinsey & Company; Atlanta (GA); Hybrid; USD 122,000 - 125,000; Full time

Job summary

McKinsey & Company is seeking a Data Engineer to power AI initiatives across client engagements. You will design scalable data pipelines and build robust data foundations for machine learning systems.

Based in offices across the US, you will work in cross-functional Agile teams with Data Scientists and ML Engineers, traveling up to 80% as needed. You will collaborate with clients to translate hypotheses into actionable data pipelines and features.

Qualifications

• Upcoming graduation between December 2026-August 2027 with a degree in an engineering discipline
• Experience in a data-focused role (internships, academic projects acceptable)
• Ability to write clean, well-documented code in a modern programming language, with a strong preference forPython and SQL
• Interest in or exposure todata engineering in the context of Agentic AI, Generative AI, Machine Learning, or Business Intelligence across different types of data formats (structured vs unstructured) and processing methods (streaming vs batch)
• Familiarity with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.), cloud platforms (AWS, Azure, GCP) and engineering tools (Pandas, Spark, dbt, LangChain, etc.)
• Exposure to modern software development practices, including version control (Git) and foundational concepts in DevOps and MLOps/LLMOps and CI/CD principles
• Exceptional time management in a complex and largely autonomous work environment
• Willingness to learn quickly and adapt to different project situations and tech stacks
• Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus
• Ability to travel up to 80% and contribute with regular in-office presence
• Strong communication skills, both verbal and written, in English and local office language(s)

Responsibilities

• Build foundational data infrastructure powering cutting-edge AI applications leveraging LLMs, retrieval systems, workflows, and emerging agentic architectures.
• 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.
• Design and build scalable, reproducible data components essential for machine learning, agentic, and autonomous AI systems.
• Collaborate with Data Scientists, ML Engineers, and industry experts to deliver AI solutions and scale enterprise data foundations.

Skills

Python

SQL

Communication skills

Team collaboration

English proficiency

Education

Bachelor's or Master's in engineering

Tools

Databricks

Snowflake

BigQuery

Pandas

Spark

dbt

LangChain

Git

CI/CD

Job description

McKinsey & Company is seeking a Data Engineer to power AI initiatives across client engagements. You will design scalable data pipelines and build robust data foundations for machine learning systems.

Based in offices across the US, you will work in cross-functional Agile teams with Data Scientists and ML Engineers, traveling up to 80% as needed. You will collaborate with clients to translate hypotheses into actionable data pipelines and features.