Senior Data Ingestion Engineer: Scalable Pipelines

Bluelight; Ciudad de Mendoza; Remote; ARS 1,800,000 - 3,000,000; Full time

Job summary

Chevron Global Services is seeking a Data Engineer in Argentina to design and maintain automated data transformation pipelines using a mix of storage and compute technologies. You will support data architecture, ingestion, and analytics across multiple data sources to empower data products and analytics teams.

The role involves collaborating with ML engineers and IT to scale solutions, contributing to internal tooling, and ensuring data quality and security across projects.

Qualifications

• BS in Computer Science, MIS, Computer Engineering or related field or equivalent experience.
• +5 years in Data Engineer role.
• Experience with ETL, big data computing, cloud data platforms, and data warehousing.

Responsibilities

• Understand business data needs and stakeholder requirements.
• Leverage data, software engineering and data science to enable data accessibility.
• Identify, acquire, cleanse, store data and develop data products aligned with architecture.
• Normalize and ingest data from multiple sources.
• Enable data scientists and collaborate with ML engineers to deploy models.
• Contribute to tool development and deployment of services.

Skills

Analytical thinking

Consulting

Critical thinking

Education

Bachelor's degree in Computer Science, MIS, Computer Engineering or related fields

Tools

Azure Data Factory

Databricks

DevOps

CI/CD

Python

Java

Ansible

Azure SQL

Azure Synapse

Git

Azure Data Lake

Logic Apps

Kimball Data Warehousing

Job description

Chevron Global Services is seeking a Data Engineer in Argentina to design and maintain automated data transformation pipelines using a mix of storage and compute technologies. You will support data architecture, ingestion, and analytics across multiple data sources to empower data products and analytics teams.

The role involves collaborating with ML engineers and IT to scale solutions, contributing to internal tooling, and ensuring data quality and security across projects.