Remote Data Engineer (AWS) - Medallion Data Platform

UNAVAILABLE; Argentina; Remote; ARS 139,474,000 - 201,463,000; Full time

Job summary

Bridgenext is seeking a Data Engineer to support the development of a modern AWS-based data platform, following Medallion Architecture principles. The role focuses on designing and implementing scalable data ingestion, transformation, and storage solutions.

Remote LATAM role, preferably in Argentina, with responsibilities spanning Bronze-Silver-Gold data layers, ingestion from multiple sources, and cost-efficient data management.

Qualifications

• 4+ years of experience in Data Engineering.
• Strong knowledge of Medallion Architecture and modern data lake practices.
• Hands-on experience with AWS services and AWS Glue Jobs.
• Experience ingesting data from diverse structured and unstructured sources.
• Strong SQL and data modeling skills.
• Experience with Lake Formation, Athena, Redshift, or EMR (preferred).

Responsibilities

• Design and implement data pipelines across Bronze, Silver, and Gold layers.
• Develop ingestion processes from multiple internal and external data sources.
• Create scalable ETL/ELT workflows using AWS-native technologies.
• Develop and manage AWS Glue Jobs and data transformation processes.
• Configure and maintain S3-based data lakes.
• Implement data quality, monitoring, and governance controls.
• Collaborate with Data Analysts and business stakeholders to meet reporting and analytics requirements.
• Optimize performance, reliability, and cost efficiency of data solutions.

Skills

Data Engineering

Medallion Architecture

AWS

S3

Glue Jobs

IAM Security

SQL

Data Modeling

Tools

AWS Glue

Amazon S3

IAM

Job description

Bridgenext is seeking a Data Engineer to support the development of a modern AWS-based data platform, following Medallion Architecture principles. The role focuses on designing and implementing scalable data ingestion, transformation, and storage solutions.

Remote LATAM role, preferably in Argentina, with responsibilities spanning Bronze-Silver-Gold data layers, ingestion from multiple sources, and cost-efficient data management.