Data Engineering Intern: Build ETL Pipelines & Insights

Procter & Gamble; Jijona; Presencial; EUR 12.000 - 15.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Relocation allowance

Competitive remuneration

Descripción de la vacante

Procter & Gamble in Jijona Plant is seeking a Data Engineering Intern to help build end-to-end pipelines, validate data quality, and align solutions with business needs. You will work with cross-functional partners to scope requirements and deliver impact from start to finish.

You'll gain hands-on experience with Azure, Python, SQL, Databricks, and CI/CD practices while contributing to data models, documentation, experiments, and performance monitoring.

Formación

• Bachelor's degree (completed or in progress) required.
• Proficiency in Python and SQL programming.
• Foundation in statistics: probability, sampling, confidence intervals.
• Understanding of regression and classification fundamentals.
• Cloud basics; Databricks experience is valued.
• Experience with Power BI or other reporting tools is valued.
• Proficient in Spanish for business; English able to conduct business.
• Valid driver's license.

Responsabilidades

• Build and optimize ETL pipelines.
• Implement data quality and validation processes.
• Contribute to data model design.
• Document solutions, patterns and standards.
• Statistical data profiling (distributions, outliers, missingness).
• Design basic experiments / A/B tests and interpret outcomes.
• Monitor pipeline and model performance (latency, data drift, metrics).
• Plan, track, and communicate progress on deliverables.

Conocimientos

Python

SQL

Statistics basics

Regression / classification

AI/ML trends

Business English

Spanish language

Educación

Bachelor's degree or in progress

Herramientas

Databricks

Power BI

Azure

Descripción del empleo

Procter & Gamble in Jijona Plant is seeking a Data Engineering Intern to help build end-to-end pipelines, validate data quality, and align solutions with business needs. You will work with cross-functional partners to scope requirements and deliver impact from start to finish.

You'll gain hands-on experience with Azure, Python, SQL, Databricks, and CI/CD practices while contributing to data models, documentation, experiments, and performance monitoring.