Data Engineer: Scalable Pipelines & Analytics

Atomic Hr; Buenos Aires; A distancia; ARS 1.200.000 - 2.200.000; Jornada completa

Descripción de la vacante

GBS Chevron Global Business Services (GBS) in Buenos Aires is seeking a Data Engineer to join the IT Organization. You will design and maintain automated data transformation pipelines across cloud and on-premise components to support data architecture and business services worldwide.

You will collaborate with data scientists and ML engineers, ensure data quality, and implement scalable data solutions using Azure Data Factory, Databricks, and SQL technologies.

Formación

• BS in Computer Science, MIS, Computer Engineering or equivalent.
• +5 years in Data Engineer role.
• Experience with ETL/ELT, data movement, analytics architecture, and cloud data platforms.
• Proficiency with Azure Data Factory, Databricks, Python/Java, and CI/CD.
• Strong analytical and problem-solving skills.

Responsabilidades

• Understand business data needs and stakeholder requirements.
• Build automated data pipelines for ingestion, prep, and analytics.
• Normalize and ingest data from multiple sources.
• Develop data products aligned with architecture patterns.
• Enable data scientists with accessible data for analytics.
• Collaborate with ML engineers to deploy models.
• Contribute to internal tooling and services.

Conocimientos

Data engineering

Big data

Data architecture

Python

Java

Cloud computing

Analytical thinking

CI/CD

Educación

BS in Computer Science/ MIS/ Computer Engineering or equivalent

Herramientas

Azure Data Factory

Databricks

Azure SQL

Azure Synapse

GIT

Azure Data Lake

Logic Apps

DevOps

Descripción del empleo

GBS Chevron Global Business Services (GBS) in Buenos Aires is seeking a Data Engineer to join the IT Organization. You will design and maintain automated data transformation pipelines across cloud and on-premise components to support data architecture and business services worldwide.

You will collaborate with data scientists and ML engineers, ensure data quality, and implement scalable data solutions using Azure Data Factory, Databricks, and SQL technologies.