AWS Data Engineer - Remote ETL & Warehouse Expert

BairesDev; Antioquia; Remote; COP 226,574,000 - 388,412,000; Full time

Benefits offered by this job

Remote work

USD compensation

Home office hardware

Flexible hours

Parental leave

Paid vacations

National holidays

Global team mentorship

Job summary

BairesDev is seeking a Data Engineer (AWS) to design and maintain scalable data pipelines and data warehouses in a globally remote setting. You will connect raw data to analytics using AWS-native services, enabling secure, scalable insights across the organization.

You will collaborate with stakeholders to translate business needs into robust data solutions, implement infrastructure as code, and uphold data quality with automated validation and monitoring.

Qualifications

• 4+ years of experience in Data Engineering or Cloud Engineering.
• Experience building data pipelines with AWS-native services like AWS Glue and Kinesis.
• Strong SQL and Python and English proficiency.

Responsibilities

• Design, build, and optimize scalable ETL/ELT pipelines using AWS services.
• Develop and maintain data warehouses on Redshift and data lakes on S3.
• Automate data workflows and infrastructure provisioning with IaC (Terraform/CloudFormation).
• Implement data models and partitioning for performance and cost efficiency.
• Ensure data quality and reliability via automated checks and monitoring.
• Collaborate with stakeholders to translate business requirements into data solutions.

Skills

Data engineering

AWS

SQL

Python

Terraform

CloudFormation

Redshift

English

Kinesis

Tools

AWS Glue

Lambda

IAM

Job description

BairesDev is seeking a Data Engineer (AWS) to design and maintain scalable data pipelines and data warehouses in a globally remote setting. You will connect raw data to analytics using AWS-native services, enabling secure, scalable insights across the organization.

You will collaborate with stakeholders to translate business needs into robust data solutions, implement infrastructure as code, and uphold data quality with automated validation and monitoring.