Remote Data Engineer (AWS) - Cloud Data Pipelines

Unavailable; Quilmes; Remote; ARS 1,200,000 - 2,400,000; Full time

Job summary

Chevron Global Business Services (GBS) in Buenos Aires, Argentina, is seeking a Data Engineer to design and maintain automated data transformation pipelines, enabling data access for analytics across the enterprise. You will work within a large IT organization delivering services globally.

The role requires 5+ years in data engineering, strong knowledge of Azure Data Factory, Databricks, and cloud data architectures, plus collaboration with ML engineers and data scientists.

Qualifications

• +5 years in Data Engineer role.
• BS in Computer Science, MIS, Computer Engineering or related field or equivalent experience.
• Experience with data engineering: ingestion, prep, validation, transformation, data products.

Responsibilities

• Understand business data needs and stakeholder requirements.
• Leverage data, software engineering, and data science to enable data access and analytics.
• Ingest, prepare, cleanse, and store data from multiple sources.
• Normalize and ingest data to support architecture patterns.
• Enable data scientists by providing accessible data for analytics models.
• Collaborate with ML Engineers to scale and deploy solutions.
• Contribute to internal tools and deployment of technical services.

Skills

5+ years experience

Analytical thinking

Consulting

Critical thinking

Education

BS in Computer Science or related field

Tools

Azure Data Factory

Databricks

Python

Java

Azure Synapse

Azure SQL

AI/ML data pipelines

DevOps / CI/CD

Job description

Chevron Global Business Services (GBS) in Buenos Aires, Argentina, is seeking a Data Engineer to design and maintain automated data transformation pipelines, enabling data access for analytics across the enterprise. You will work within a large IT organization delivering services globally.

The role requires 5+ years in data engineering, strong knowledge of Azure Data Factory, Databricks, and cloud data architectures, plus collaboration with ML engineers and data scientists.