Data Engineer

GFT Technologies SE; Girardot; On-site; COP 60,000,000 - 90,000,000; Full time

Job summary

GFT Technologies SE is seeking a Data Engineer (ENG) to design, build, and maintain scalable data solutions. You will develop data ingestion, transformation, and storage processes for analytics and business initiatives.

Join a team leveraging modern data architectures and cloud platforms, with emphasis on automation, data quality, and reliability across data pipelines and analytics platforms.

Qualifications

• Experience designing, building, and maintaining scalable data solutions.
• Proficient in data ingestion, transformation, and storage processes.
• Knowledge of modern data architectures and cloud platforms.
• Experience with Python and SQL.
• Knowledge of data governance and data security concepts.

Responsibilities

• Develop data ingestion and ETL/ELT pipelines.
• Build data models and maintain data quality.
• Collaborate on analytics initiatives and BI tools.
• Operate in cloud environments and automate pipelines.

Tools

Python Development

Data Modeling

ETL/ELT Processes

Data Pipeline Design

AWS (Glue, S3)

Workflow Orchestration (Airflow)

Relational Databases (SQL)

NoSQL Databases

Data Quality

Modern Data Architectures

Analytics Platforms (Redshift/Snowflake)

Git & Version Control

CI/CD for Data Pipelines

AI Tools for development

Job description

Data Engineer (ENG)

Data Engineer with experience designing, building, and maintaining scalable and efficient data solutions. Responsible for developing data ingestion, transformation, and storage processes, ensuring data availability, quality, and reliability for analytics and business initiatives. Experienced in modern data architectures, pipeline automation, and cloud platforms, enabling organizations to generate value through data-driven solutions.

Technical Skills

• Python Development
• Data Modeling
• ETL/ELT Processes
• Data Pipeline Design and Development
• AWS (Glue, S3)
• Workflow Orchestration (Airflow, AWS Step Functions, or similar)
• Relational Databases (SQL Server, PostgreSQL, MySQL, Oracle)
• NoSQL Databases (MongoDB, DynamoDB, Cassandra, or similar)
• Data Quality and Validation
• Modern Data Architectures (Data Lake, Lakehouse, and Data Warehouse)
• Analytical Platforms (Redshift, Snowflake, or similar)
• Git and Version Control
• CI/CD for Data Pipelines
• Experience using Artificial Intelligence tools to support development, testing, and documentation

Nice to Have

• Knowledge of dbt or similar data transformation frameworks.
• Experience in banking or financial services projects.
• Knowledge of lending products and financial data ecosystems.
• Understanding of data governance, security, and data lineage.

Data Engineer (ESP)

Profesional con experiencia en el diseño, construcción y mantenimiento de soluciones de datos escalables y eficientes. Responsable de desarrollar procesos de ingesta, transformación y almacenamiento de datos, garantizando su disponibilidad, calidad y confiabilidad para iniciativas analíticas y de negocio. Cuenta con experiencia en arquitecturas modernas de datos, automatización de pipelines y plataformas cloud, contribuyendo a la generación de valor a través de los datos.

Skills Técnicos

• Desarrollo en Python
• Modelado de Datos
• Procesos ETL/ELT
• Diseño y Desarrollo de Data Pipelines
• AWS (Glue, S3)
• Orquestación de Procesos (Airflow, AWS Step Functions o similares)
• Bases de Datos Relacionales (SQL Server, PostgreSQL, MySQL, Oracle)
• Bases de Datos No Relacionales (MongoDB, DynamoDB, Cassandra o similares)
• Calidad y Validación de Datos
• Arquitecturas Modernas de Datos (Data Lake, Lakehouse y Data Warehouse)
• Plataformas Analíticas (Redshift, Snowflake o similares)
• Git y Control de Versiones
• CI/CD para Data Pipelines
• Manejo de herramientas de Inteligencia Artificial para apoyar el desarrollo, las pruebas y la documentación

Deseable

• Conocimiento de dbt o frameworks similares de transformación de datos.
• Experiencia en proyectos del sector bancario o financiero.
• Conocimiento de productos de crédito y ecosistemas de datos financieros.
• Conocimientos de gobierno, seguridad y linaje de datos.