Senior Data Engineer, Cloud Pipelines & Analytics

Holcim; Quilmes; In loco; ARS 1.000.000 - 1.500.000; Tempo pieno

Vantaggi offerti da questo lavoro

Relocation support

Descrizione del lavoro

Chevron Global Business Services (GBS) in Buenos Aires (Puerto Madero), Argentina, seeks a Data Engineer to build and maintain automated data transformation pipelines using a variety of storage and compute technologies to support data architecture design.

Responsibilities include ingesting, preparing, and validating data; enabling data scientists with accessible data; and collaborating with ML engineers to scale solutions. Relocation may be considered, with expat assignments not offered.

Competenze

• BS in Computer Science, MIS, Computer Engineering or related field, or equivalent experience.
• 5+ years in Data Engineer role.
• Experience with: data ingestion, preparation, transformation, and analytics.
• Knowledge of cloud data platforms and security technologies.
• Experience with ETL/ELT tools and data warehousing methodologies.

Mansioni

• Understand business use of data and stakeholder requirements to support processes and objectives.
• Leverage data engineering and analytics techniques to create business value and data accessibility.
• Identify, acquire, cleanse, and prepare data; develop data products aligned with architecture patterns.
• Normalize and ingest data from multiple sources.
• Enable data scientists by making data available for analytics and model deployment.
• Collaborate with ML engineers to scale and deploy data/ML solutions.

Conoscenze

Data engineering

Analytics

Problem solving

Team collaboration

Formazione

Bachelor’s degree in CS or related field

Strumenti

Azure Data Factory

Databricks

Python

Azure SQL

Azure Synapse

Git

CI/CD

Ansible

Microsoft Data Flows

Data Lake

Descrizione del lavoro

Chevron Global Business Services (GBS) in Buenos Aires (Puerto Madero), Argentina, seeks a Data Engineer to build and maintain automated data transformation pipelines using a variety of storage and compute technologies to support data architecture design.

Responsibilities include ingesting, preparing, and validating data; enabling data scientists with accessible data; and collaborating with ML engineers to scale solutions. Relocation may be considered, with expat assignments not offered.