Data Engineering on GCP

Worldwide | Sept. 1, 2026

Report as Closed

Company: DSAC Chile

Country: Worldwide

Salary: $30,000 - $42,000

Type: Remote

Employment: Full-time

Description: DSAC is a Chilean technology company specializing in the development of technology solutions, artificial intelligence, cybersecurity, and automation for companies seeking to improve their efficiency and make a real impact on their business. None

Education Level

Bachelor’s degree or professional technical degree in Computer Engineering, Civil Engineering, Computer Science, or related fields.

Minimum Requirements (Mandatory)

5+ years of experience in data engineering or similar roles.
Verifiable experience developing data pipelines in cloud environments.
Solid experience working with Google Cloud Platform (GCP). Proficiency in:
BigQuery
Dataflow
Pub/Sub
Cloud Storage
Dataproc
Composer
Experience in:
ETL/ELT processes
Data lakes and data warehouses
Data integration and transformation
Batch and near real-time pipelines
Advanced SQL skills.
Experience in the financial industry, banking, or fintech.
Experience working with sensitive data.

The role will be responsible for building and optimizing scalable data pipelines, collaborating with various technical and functional teams, and ensuring best practices for quality, security, and efficiency in data handling, primarily in the financial industry and when processing sensitive information.

Description

Design, develop, and maintain data engineering solutions on Google Cloud Platform (GCP), ensuring the proper ingestion, transformation, processing, and availability of data for the business’s analytical and operational initiatives.

Key Responsibilities: Data Engineering and Development

Develop and maintain batch and near real-time data pipelines on Google Cloud Platform (GCP).
Implement processes for data ingestion, transformation, and delivery for analytics and operational use.
Build scalable and efficient ETL/ELT flows.
Participate in the optimization of data processing and storage processes.
Collaborate on the modeling and structuring of analytical datasets.
Monitor and ensure the correct execution of pipelines and automated processes.

GCP Ecosystem

Work with tools from the GCP ecosystem such as:
BigQuery
Cloud Storage
Dataflow
Pub/Sub
Dataproc
Cloud Composer
Develop data integration solutions across multiple sources.
Implement cloud-native development best practices.
Participate in data platform modernization initiatives.

Quality, Governance, and Security

Implement basic data quality and validation controls.
Ensure traceability and consistency in data processes.
Apply best practices for security and access control.
Work with sensitive data in accordance with regulatory and compliance guidelines.
Collaborate with data governance and architecture teams.

Collaborative Work

Translate functional requirements into technical data solutions.
Work closely with business, analytics, and technology teams.
Participate in initiatives related to: *Customers *Financial products *Payments *Fraud *Risk

Work Schedule / Salary Range