Remote Data Engineer: Scalable Data Pipelines & Analytics

Fullstack; Quilmes; Remoto; ARS 1.000.000 - 1.800.000; Tempo pieno

Descrizione del lavoro

Chevron Global Business Services (GBS) in Buenos Aires, Argentina, is seeking a Data Engineer to join the IT Organization. You will design and maintain automated data transformation pipelines using Azure and cloud technologies to support data architecture and analytics across the business.

The role requires 5+ years in data engineering, strong skills in Azure Data Factory, Databricks, Python and SQL, and the ability to collaborate with ML teams to scale models.

Competenze

• BS in Computer Science, MIS, CE or related field or equivalent experience.
• 5+ years in Data Engineer role.
• Knowledge of data ingestion, preparation, validation; data movement and transformation; analytics solution architecture; big data computing; cloud computing; security; and software engineering using Azure/DataFactory, Databricks, Python, Java, and related tools.

Mansioni

• Understand business data needs and stakeholder requirements.
• Leverage data, software engineering and data science techniques to enable access; includes ingestion, preparation and analytics processing.
• Identify, acquire, cleanse & prepare, store data and develop data products aligned with defined architecture patterns.
• Normalize and ingest data from multiple sources.
• Enable data scientists by providing data for analytics models; contribute to models.
• Collaborate with ML Engineers to scale and deploy solutions including models, documentation, and integration.

Conoscenze

Analytical thinking

Critical thinking

Data storytelling

Formazione

BS in Computer Science or related field

Equivalent experience

Strumenti

Azure Data Factory

Databricks

Python

Java

CI/CD Pipelines

Azure SQL

Azure Synapse

Git

Azure Data Lake

Descrizione del lavoro

Chevron Global Business Services (GBS) in Buenos Aires, Argentina, is seeking a Data Engineer to join the IT Organization. You will design and maintain automated data transformation pipelines using Azure and cloud technologies to support data architecture and analytics across the business.

The role requires 5+ years in data engineering, strong skills in Azure Data Factory, Databricks, Python and SQL, and the ability to collaborate with ML teams to scale models.