Data Engineer (ETL, Airflow) - Remote Growth

AgileEngine; Sur; Presencial; COP 60.000.000 - 120.000.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Growth without limits

Competitive compensation

Flexibility: 100% remote with flexible

Meaningful, modern projects

Collaborative culture

Well-being & support

Descripción de la vacante

AgileEngine seeks a Data Engineer to own ETL pipelines powering analytics for colleges and universities. You will design and maintain data workflows using SQL, Python, and Apache Airflow, moving data from source systems into a cloud data warehouse.

Collaborate with client teams and analysts to gather requirements, adapt shared pipelines for individual clients, and contribute to platform modernization with new data technologies.

Formación

• 3-4 years of experience in data engineering or related software engineering role.

Responsabilidades

• Design, build, and maintain ETL pipelines and data workflows across multiple environments (development, staging, and production).
• Implement and extend data models and datasets to support analytical and reporting needs.
• Adapt and customize shared data pipelines for individual clients while maintaining a clean, reusable codebase.
• Monitor and support production data pipelines, investigate failures, and deliver fixes in a timely manner.
• Write and maintain database DDL, data validation queries, and deployment scripts.
• Contribute to platform modernization initiatives, including infrastructure upgrades and adoption of new data technologies.
• Collaborate with client teams, analysts, and stakeholders to gather requirements and deliver solutions.

Conocimientos

SQL

Python

Airflow

ETL patterns

Cloud data warehouse design

Git/GitLab

Docker

Data management

Requirements analysis

English

Herramientas

Amazon Redshift

Snowflake

BigQuery

Spark

Tableau

PowerBI

Descripción del empleo

AgileEngine seeks a Data Engineer to own ETL pipelines powering analytics for colleges and universities. You will design and maintain data workflows using SQL, Python, and Apache Airflow, moving data from source systems into a cloud data warehouse.

Collaborate with client teams and analysts to gather requirements, adapt shared pipelines for individual clients, and contribute to platform modernization with new data technologies.