Senior Data Engineer - SQL Server & Power BI (Healthcare)

Communities Tech; Buenos Aires; On-site; ARS 1,800,000 - 3,200,000; Full time

Job summary

Chevron Corporation in Buenos Aires, Argentina, is seeking a Data Engineer to join the IT Organization. The role focuses on building and maintaining automated data transformation pipelines, enabling data access for analytics and decision-making across the enterprise.

The candidate will work with Azure-based tools (Data Factory, Databricks, Synapse) and collaborate with data scientists and ML engineers to scale solutions for big data workloads.

Relocation options may be considered.

Qualifications

• BS in Computer Science, MIS, or related field or equivalent experience.
• 5+ years in Data Engineer roles with data pipelines and ETL.
• Experience with Azure data services and cloud computing platforms.
• Knowledge of data warehouse methodologies and data security technologies.

Responsibilities

• Understand business data requirements to support processes and objectives.
• Develop and maintain automated data transformation pipelines.
• Ingest, prepare, and validate data from multiple sources.
• Enable data scientists by providing accessible data for analytics models.
• Collaborate with ML engineers to scale and deploy solutions.

Skills

Big data processing

ETL design

Data governance

analytics collaboration

Python

Java

Cloud computing

DevOps

CI/CD

Analytical thinking

Education

BS in Computer Science or related field

Tools

Azure Data Factory

Databricks

Azure Synapse

Azure SQL

Azure Data Lake

Logic Apps

GIT

ADO

Python

Java

Ansible

Microsoft Data Flows

Job description

Chevron Corporation in Buenos Aires, Argentina, is seeking a Data Engineer to join the IT Organization. The role focuses on building and maintaining automated data transformation pipelines, enabling data access for analytics and decision-making across the enterprise.

The candidate will work with Azure-based tools (Data Factory, Databricks, Synapse) and collaborate with data scientists and ML engineers to scale solutions for big data workloads.

Relocation options may be considered.