Cloud Data Engineer — Build Scalable Pipelines on GCP

Capgemini Engineering; Aguascalientes; Presencial; MXN 420.000 - 860.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Diversity & inclusion

Continuous learning

Mentorship

Employee networks

Fun and Team spirit

Descripción de la vacante

Capgemini Engineering in Mexico is seeking a Data Engineer to develop and maintain data pipelines that support analytics and business reporting. You will optimize ETL/ELT processes, validate data quality, and collaborate with Agile teams to deliver platform enhancements.

We expect 4–5 years of data engineering experience, strong Python, PySpark, SQL skills, and experience with BigQuery, Dataproc, and Cloud Composer in GCP.

Formación

• 4-5 years of experience in Data Engineering, Data Development, or related data-focused roles.
• Hands-on experience with Python, PySpark, SQL, and cloud-based data processing environments.
• Familiarity with BigQuery, Dataproc, and Cloud Composer, with a willingness to expand expertise in GCP services.
• Understanding of ETL/ELT processes, data pipelines, data quality, and data transformation concepts.
• Strong problem-solving skills, eagerness to learn, and ability to work effectively in collaborative Agile environments.

Responsabilidades

• Develop and maintain data pipelines that support analytics and business reporting solutions.
• Build and enhance ETL/ELT processes using cloud-based data technologies.
• Perform data validation, testing, and troubleshooting activities to ensure data quality and reliability.
• Optimize SQL queries and support improvements in data processing performance.
• Collaborate with Agile teams to deliver new features, deployments, and platform enhancements.

Conocimientos

Python

PySpark

SQL

Cloud data processing

Herramientas

BigQuery

Dataproc

Cloud Composer

Descripción del empleo

Capgemini Engineering in Mexico is seeking a Data Engineer to develop and maintain data pipelines that support analytics and business reporting. You will optimize ETL/ELT processes, validate data quality, and collaborate with Agile teams to deliver platform enhancements.

We expect 4–5 years of data engineering experience, strong Python, PySpark, SQL skills, and experience with BigQuery, Dataproc, and Cloud Composer in GCP.