AI Data Engineer: Build Scalable Data Pipelines

McKinsey; Bogotá; On-site; COP 60,000,000 - 120,000,000; Full time

Job summary

McKinsey is hiring for a Data Engineer role focused on building scalable data foundations for AI systems. You will work with LLMs, retrieval systems, and agentic architectures, designing data pipelines and secure environments while collaborating with Data Scientists and domain experts in a global setting.

We value experience with Python, SQL, Databricks/Snowflake, and cloud platforms, plus strong communication in English and Spanish.

Qualifications

• Degree in Computer Science or Engineering or equivalent.
• 2+ years in a data-focused role, internships or projects accepted.
• Clean, well-documented code in Python/SQL; strong problem-solving.
• Exposure to AI data engineering and various data formats.
• Familiarity with Databricks/Snowflake/BigQuery and cloud platforms.

Responsibilities

• Build data infrastructure powering AI applications and LLMs.
• Design scalable data pipelines and secure data environments.
• Collaborate with data scientists and engineers across teams.
• Translate hypotheses into engineered features for AI systems.

Skills

Python

SQL

Data engineering

Git

Cloud platforms

Education

Degree in Computer Science/Engineering

Tools

Databricks

Snowflake

BigQuery

Pandas

Spark

Job description

McKinsey is hiring for a Data Engineer role focused on building scalable data foundations for AI systems. You will work with LLMs, retrieval systems, and agentic architectures, designing data pipelines and secure environments while collaborating with Data Scientists and domain experts in a global setting.

We value experience with Python, SQL, Databricks/Snowflake, and cloud platforms, plus strong communication in English and Spanish.