Remote Data Engineer: Cloud Analytics & Pipelines

Uptalent.Io; Quilmes; Remoto; ARS 92.724.000 - 146.813.000; Tempo pieno

Descrizione del lavoro

Chevron Global Business Services (GBS) in Buenos Aires, Argentina is seeking a Data Engineer to build and maintain automated data transformation pipelines. The role supports data architecture design by integrating diverse storage and compute technologies and enabling scalable data products for analytics teams.

The candidate will collaborate with ML engineers, scale models, and contribute to internal tooling while adhering to best practices in software engineering and DevOps.

Competenze

• BS in Computer Science, MIS, Computer Engineering or related field (or equivalent experience).
• +5 years in Data Engineer role.
• Experience with Azure Data Factory, Databricks, Python/Java, and data warehousing concepts.
• Knowledge of analytics solution architecture and cloud computing.

Mansioni

• Understand business use of data and stakeholder requirements to support processes and objectives.
• Leverage data, software engineering, and data science techniques to create business value through data accessibility.
• 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, making data available for advanced analytics models and contributing to models.
• Work with ML Engineer to scale and deploy solution including model, documentation, training, integration.
• Contributing to the inner source development of foundational tools, and/or the deployment of technical services.

Conoscenze

Python

Java

Azure Data Factory

Databricks

Azure Synapse

CI/CD

Git

Azure Data Lake

ETL

Formazione

BS in Computer Science or related field

Strumenti

Git

ADO (Azure DevOps)

Azure Data Lake

Azure Analysis Services

Logic Apps

Microsoft Data Flows

Descrizione del lavoro

Chevron Global Business Services (GBS) in Buenos Aires, Argentina is seeking a Data Engineer to build and maintain automated data transformation pipelines. The role supports data architecture design by integrating diverse storage and compute technologies and enabling scalable data products for analytics teams.

The candidate will collaborate with ML engineers, scale models, and contribute to internal tooling while adhering to best practices in software engineering and DevOps.