Remote Senior Data Engineer: Etl

Buenos Aires, Buenos Aires, Argentina
Full time
R
Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Job Description
GBS Chevron Global Business Services (GBS), located in Buenos Aires (Puerto Madero), Argentina, is accepting applications for the position of Data Engineer. Successful candidates will join the IT Organization, which is part of a multifunction service and technical center with a workforce of more than 1800 employees that deliver business services and solutions to the corporation across the globe.
Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Responsibilities include:

• Understand business use of data and stakeholder requirements to support work processes and strategic business objectives
• Leverage data, software engineering, and data science techniques to create business value through data accessibility. Includes data ingestion, data preparation and analytics processing.
• Identify, acquire, cleanse & prepare, store data and develop data products aligned with defined architecture patterns
• Responsible for normalizing and ing... (truncated for brevity)

Required Qualifications:
+ BS in Computer Science, Management Information Systems, Computer Engineer or related fields or equivalent experience.
+ +5 years in Data Engineer Role
+ Knowledge and/or experience with: data acquisition, preparation and validation; data movement and transformation; analytics solution architecture; big data computing; cloud computing, core data architecture; information security technologies and software engineering using technologies such as: Azure Data Factory (ETL), Databricks, DevOps, CI/CD Pipeline Deployment, Python, Java, Ansible, Azure SQL, Azure Synapse, GIT, ADO, Azure Data Lake, Azure Analysis Services, Logic Apps, Microsoft Data Flows, Kimball Data Warehousing Methodology
+ Analytical thinking, Consulting, Critical Thinking

Relocation Options

Relocation may be considered.

International Considerations

Expatriate assignments will not be considered.

Chevron regrets that it is unable to sponsor employment Visas or consider individuals on time-limited Visa status for this position

Chevron participates in E-Verify in certain locations as required by law.

Chevron Corporation is one of the world's leading integrated energy companies. Through its subsidiaries that conduct business worldwide, the company is involved in virtually every facet of the energy industry. Chevron explores for, produces and transports crude oil and natural gas; refines, markets and distributes transportation fuels and lubricants; manufactures and sells petrochemicals and additives; generates power; and develops and deploys technologies that enhance business value in every aspect of the company's operations. Chevron is based in Houston, Texas. More information about Chevron is available at .

Chevron is an Equal Opportunity / Affidantiive Action employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status, or other status protected by law or regulation.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you

ABOUT THE ROLE

We are looking for a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation.

WHAT YOU WILL DO

• Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.
• Build and operationalize agentic workflows to automate data engineering and operational processes such as data validation, issue identification, troubleshooting, and workflow execution.
• Integrate agentic capabilities with existing Databricks, GCP, BigQuery, and Delta Lake environments.
• Develop data pipelines and processing solutions to support new business requirements and datasets.
• Build reusable frameworks and components that can be leveraged across multiple data engineering and business use cases.
• Implement data quality checks, monitoring, validation, exception handling, and production controls.
• Optimize PySpark and SQL workloads for performance, reliability, and scalability. <