Data Engineer II — AI & Agentic Data Pipelines

McKinsey; Newark (NJ); On-site; USD 147,000 - 150,000; Full time

Job summary

McKinsey & Company seeks a Data Engineer in North America to build foundational data infrastructure powering AI applications, including LLMs, retrieval systems, and agentic architectures.

You will design scalable data pipelines, manage secure data environments, and prepare data for AI-driven systems while collaborating with cross-functional teams and clients across industries. This role offers growth as a client-facing technologist within a global Data Engineering community.

Qualifications

• U.S. Citizenship is a requirement for this role (you must be able to be staffed on Critical Industries work which includes Government, Defense, Aerospace, Utilities, etc.)
• 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 English and local office language(s)
• Willingness to travel as required

Responsibilities

• Build foundational data infrastructure powering AI applications, including LLMs, retrieval systems, workflows, and agentic architectures
• Design and maintain scalable data pipelines and secure data environments; prepare data for AI-driven systems
• Collaborate with cross-functional teams and clients to deliver production-ready data foundations for next‑generation AI capabilities
• Translate hypotheses into engineered features; contribute to R&D initiatives focusing on innovating and scaling AI
• Work with Data Scientists, ML Engineers, and industry experts to deliver enterprise AI solutions across industries
• Participate in Agile teams and help ensure data solutions are reliable, scalable, and secure

Skills

Python

SQL

Data engineering

MLOps/LLMOps

CI/CD

LangChain

Cloud data platforms

Education

Bachelor's degree in Computer Science/Engineering

Tools

Spark

dbt

LangChain

Pandas

Databricks

Snowflake

BigQuery

Terraform

LangSmith

Opik

Langfuse

AWS

Azure

GCP

Job description

McKinsey & Company seeks a Data Engineer in North America to build foundational data infrastructure powering AI applications, including LLMs, retrieval systems, and agentic architectures.

You will design scalable data pipelines, manage secure data environments, and prepare data for AI-driven systems while collaborating with cross-functional teams and clients across industries. This role offers growth as a client-facing technologist within a global Data Engineering community.