Junior Data Engineer – Oracle Cloud (OCI) | International Project (Chile)

Talanto; Santiago; Híbrido; CLP 13.392.000 - 25.668.000; Jornada completa

Descripción de la vacante

Talanto is seeking junior Data Engineers to join an international project for a leading telecom in Chile. You will build data ingestion and transformation pipelines using Python and Spark within Oracle Cloud Infrastructure (OCI), turning raw data into business-ready datasets for BI and analytics.

You will support production operations, monitor data quality, and collaborate with teams across Chile. Candidates with 1+ year in data projects and strong Python skills are preferred; OCI exposure is a

Formación

• 1+ year of experience in data projects (ingestion/transformation/provisioning).
• Strong knowledge of Python.
• Exposure to cloud environments, preferably Oracle Cloud Infrastructure (OCI).
• Availability to work aligned with the Chilean time zone.

Responsabilidades

• Develop, implement, and troubleshoot data ingestion and transformation pipelines using Python and Spark within OCI.
• Transform raw telecom data into business-ready datasets for BI and analytics.
• Support production operations by investigating failures, monitoring data quality, and optimizing performance and resources.
• Collaborate with teams in Chile, participating in architecture discussions and continuous improvement.

Conocimientos

Python

Spark

Spanish (conversational)

Herramientas

Oracle OCI

Descripción del empleo

Python Data Science Spark

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Project OverviewWe are looking for Junior Data Engineers to join an international project for a leading telecommunications company in Chile. The client is currently building its enterprise Lakehouse platform on Oracle Cloud Infrastructure (OCI), centralizing business data and supporting the company’s broader modernization strategy. The roadmap includes migrating additional data sources, executing transformation initiatives, and provisioning data through OCI services such as Dataflow, Data Science, AI Data Platform, and Autonomous Data Warehouse, with future integration into Oracle’s AI platform ecosystem. This is an excellent opportunity for junior professionals looking to strengthen their experience in cloud-based data engineering within a large-scale international environment.

Key Responsibilities

• Develop, implement, and troubleshoot data ingestion and transformation pipelines using Python and Spark within Oracle Cloud Infrastructure (OCI)
• Transform raw telecommunications data into business-ready datasets and support data provisioning for BI and analytics purposes
• Support production operations by investigating failures, monitoring data quality, and optimizing performance and resource usage
• Collaborate with teams and stakeholders based in Chile, participating in architecture discussions and continuous improvement initiatives

Mandatory Requirements

• 1+ year of experience in Data projects, particularly in data ingestion, transformation, or provisioning
• Strong knowledge of Python
• Exposure to cloud environments, preferably Oracle Cloud Infrastructure (OCI)
• Availability to work aligned with the Chilean time zone (Portugal schedule: typically 12:00–21:00 or 14:00–23:00 depending on daylight savings)
• Ability to communicate in Spanish (for Portuguese candidates, fluent Spanish is not mandatory, but conversational level and ability to communicate comfortably are required)
• Remote work availability

Nice-to-Have Skills

• Good understanding of Oracle Cloud Infrastructure (OCI) architecture and services
• Experience with Spark and distributed data processing environments
• Previous exposure to BI or analytics-oriented data platforms

Candidate Profile

• Junior-level professionals with up to 3 years of professional experience
• Strong willingness to learn and grow within international cloud and data environments
• Proactive mindset with good problem-solving and collaboration skills

Preferred Locations

Preference will be given to candidates based in:PortugalChilePeru

The range shows the lower and upper market bands: 25% of vacancies pay below the first value, the median is the typical salary, and 75% marks the upper band.