About the Role
Responsible for the daily operation,configuration, monitoring, and maintenance of the cloud BigData service field in the Latin American region, and serves as the second-line support for handling demand changes,customer incident,and alarm tickets.
Responsible for the active operation and maintenance of a single cloud service, including SLO construction, process optimization, capacity management, standardized transformation, disaster recovery construction, daily drills, etc., by developing corresponding automation plug‐ins on the tool platform to optimize operation and maintenance efficiency and availability.
Professional Knowledge
Understand the core design principles of Hadoop, including HDFS architecture and read/write flows, YARN's resource scheduling model, and the MapReduce computing paradigm.
Understand basic data warehouse concepts (, fact tables, dimension tables) and the architecture of Hive, especially the role of the Metastore and how HQL is translated into computation jobs.
Understand the core concepts of Spark, such as RDD resilience and fault tolerance, the advantages of DataFrames for structured data processing, and the execution flow of a Spark job.
Strong knowledge of Linux operating systems and environments.
A self-starter able to work independently but comfortable working in a team environment.
Ability to quickly learn new or unfamiliar technology and products using documentation and internet resources.
Skills
General skills of the operating system: Familiar with the daily operation and maintenance of the operating system, master the troubleshooting and handling of common operating system problems, experience in using shell/python for automated operation and maintenance is preferred;
General troubleshooting skills: System Log analysis, Packages catch and Analysis, Traffic analysis, Monitor design and optimize
Ability to write common HQL/SQL for data querying, joins, and simple aggregations.
Possess basic troubleshooting skills to identify the preliminary cause of MapReduce/Spark job failures (, OOM, data skew) by analyzing YARN UI and log files.
Qualifications
Proficient in English and can use it as a working language (Mandatory)
+1 Year of experience.
Must be available to work On-Site.
AWS/Azure/Google Cloud Certification or other related certificates
Location
Buenos Aires, Buenos Aires, Argentina
Job Type
Full time
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Job Description
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.
**GBS Chevron General 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 **** 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
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 ingesting 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.
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
Visa Policy
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 / Affrrmative 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.
AgileEngine Overview
AgileEngine is an Inc. **** company that creates award‐winning software for Fortune 500 brands and trailblazing startups across 17+ industries.
We rank among the leaders in areas like application development and AI/ML, and our people‐first culture has earned us multiple Best Place to Work awards.
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 Senior Data Engineer to design and maintain data pipelines and automation systems that power cloud cost visibility, attribution, and performance insights for a Cloud Economics team.
You will build scalable ELT/ETL workflows using Python, SQL, dbt, and Airflow across AWS services including Glue, Athena, and Aurora alongside Snowflake, optimizing for performance, reliability, and cost efficiency.
The role partners closely with Engineering and Finance stakeholders to support cost optimization initiatives and usage‐based decision‐making.
WHAT YOU WILL DO
Design, build, and maintain the Cloud Economics team's data pipelines and automation systems.
Build and maintain scalable data pipelines and datasets that power cloud cost visibility, attribution, and performance insights.
Design and implement data models and ingestion frameworks to support large‐scale telemetry and usage data.
Develop tooling that enables cost‐aware decision‐making across Product, Engineering, and Finance stakeholders.
Optimize data systems for performance, reliability, and cost efficiency (query tuning, storage strategies, compute optimization).
Partner with Engineering and Finance teams to support cost optimization initiatives and usage‐based insights.
Ensure data quality, validation, and auditability across end‐to‐end data workflows.
MUST HAVES
4+ years of experience in Data Engineering roles.
Strong Data Engineering foundation with proven experience building and maintaining end‐to‐end ELT/ETL pipelines in cloud environments.
Strong SQL and Python.
Experience with orchestration tools such as dbt, Airflow, or Dagster.
AWS data ecosystem experience, including AWS Glue, Amazon Athena, and Amazon Aurora.
Experience with Snowflake.
Strong data modeling and large‐scale data processing experience.
Experience with CI/CD, version control, Infrastructure as Code (
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📌 Data Engineer (Senior) - Etl (Python+Snowflake) - Remote, Latin América
🏢 Bluelight Consulting
📍 Buenos Aires