Data Engineer Associate: Hybrid Cloud Pipelines & BI

Scotiabank; Bogotá ciudad; Híbrido; COP 30.000.000 - 60.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Descripción de la vacante

Scotiabank is seeking a junior Data Engineer to contribute to the development of data assets and models for International Banking Analytics. You will build scalable data pipelines for on-prem and cloud environments and collaborate with BI teams to deliver data for PowerBI-driven insights.

The role requires knowledge of SQL, Python, Airflow, and cloud technologies, with a focus on reliability and efficient data delivery across international teams. Hybrid work model expected.

Formación

• Bachelor's degree in Computer Science or Engineering.
• Experience as a junior Data Engineer or Technical Business Analyst.
• Knowledge of SQL, Python, Git, Airflow; Spark and Docker are a plus.
• Experience with Big Data and Cloud Technologies is preferred.
• English proficiency at B2 level is desirable.

Responsabilidades

• Participate in data engineering and transformation design for scalable solutions.
• Develop data pipelines for on-prem and cloud environments.
• Collaborate with BI teams and set up data pipelines to PowerBI.
• Contribute to data delivery for high-visibility projects across the bank.
• Support onboarding and training of new users in the data engineering community.

Conocimientos

SQL

Python

Airflow

Git

Power BI

BigQuery

Docker

Spark

Educación

Bachelor's degree in Computer Science or Engineering

Herramientas

Cloud computing

Airflow

GitHub/JIRA/Confluence

Descripción del empleo

Scotiabank is seeking a junior Data Engineer to contribute to the development of data assets and models for International Banking Analytics. You will build scalable data pipelines for on-prem and cloud environments and collaborate with BI teams to deliver data for PowerBI-driven insights.

The role requires knowledge of SQL, Python, Airflow, and cloud technologies, with a focus on reliability and efficient data delivery across international teams. Hybrid work model expected.