AI Data Engineer: Build Scalable Data Pipelines

McKinsey; Monterrey; Hybrid; MXN 600,000 - 900,000; Full time

Job summary

McKinsey is seeking a data engineer based in Monterrey to build scalable data foundations powering AI applications and agentic systems. You will design pipelines, manage secure environments, and work with data scientists and ML engineers across client projects.

You will apply Python/SQL, Databricks, Snowflake, and modern data tools in a collaborative, Agile setting, helping translate hypotheses into engineered features and advancing AI capabilities for clients worldwide.

Qualifications

• Bachelor's level degree in CS/Engineering or equivalent experience.
• 2+ years in a data-focused role with hands-on projects.
• Proficient in Python and SQL with clean, well-documented code.

Responsibilities

• Build scalable data infrastructure powering AI apps and LLMs.
• Design and maintain data pipelines and secure data environments.
• Collaborate with Data Scientists, ML Engineers, and clients to deliver AI solutions.

Skills

Python

SQL

Data engineering

English & Spanish

Git

Analytical thinking

Cloud platforms

Team collaboration

Education

Degree in Computer Science/Engineering

2+ years data-focused experience

Tools

Databricks

Snowflake

BigQuery

Pandas

Spark

dbt

LangChain

CI/CD

MLOps

LLMOps

Job description

McKinsey is seeking a data engineer based in Monterrey to build scalable data foundations powering AI applications and agentic systems. You will design pipelines, manage secure environments, and work with data scientists and ML engineers across client projects.

You will apply Python/SQL, Databricks, Snowflake, and modern data tools in a collaborative, Agile setting, helping translate hypotheses into engineered features and advancing AI capabilities for clients worldwide.