Global Supply Chain BI Engineer

Ford México; Naucalpan de Juárez; Presencial; MXN 420.000 - 720.000; Jornada completa

Descripción de la vacante

Ford of Mexico is seeking an Analytics Engineer to bridge manufacturing operations and data ecosystems. You will design, optimize, and govern data pipelines and semantic models to deliver real-time insights for supply chain and quality teams.

You will implement ETL/ELT processes using SQL and Python, collaborate across functions, and explore AI and automation to streamline reporting and governance while maintaining a scalable data architecture.

Formación

• Bachelor’s degree in a data-focused technical field or equivalent experience.
• 2–3 years in Analytics Engineering, Data Engineering, or BI in industrial settings.
• Proficient English communication of complex data insights.

Responsabilidades

• Design and optimize centralized semantic data models for a unified single source of truth.
• Develop and automate ETL/ELT pipelines using SQL and Python to BI platforms.
• Collaborate with supplier quality and technical support on data-driven root-cause analyses.
• Translate engineering data into clear, high-level reporting for planning and budget tracking.
• Identify and implement automation and AI solutions to improve workflows and documentation.
• Establish and maintain data governance and scalable star/snowflake schemas.

Conocimientos

Data modeling

DAX

Power Query

SQL

Python

Star/Snowflake schemas

Data governance

Educación

Bachelor’s degree in Mechatronics, Robotics, Computer Science, Industrial Engineering (with a data focus)

Herramientas

Power BI

Tableau

dbt

Snowflake

Azure Databricks

Python

SQL

Descripción del empleo

Ford of Mexico is seeking an Analytics Engineer to bridge manufacturing operations and data ecosystems. You will design, optimize, and govern data pipelines and semantic models to deliver real-time insights for supply chain and quality teams.

You will implement ETL/ELT processes using SQL and Python, collaborate across functions, and explore AI and automation to streamline reporting and governance while maintaining a scalable data architecture.