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Strong Python programming skills for data engineering tasks
Shape reliable, scalable data pipelines with Snowflake, AWS, Airflow, and dbt; collaborate across teams to turn data into actionable insights and AI-powered improvements.
About The Role
This role supports data-driven decision making by building reliable, scalable data pipelines and enabling analytics across the organization.
You'll work with modern data stack tools to ensure strong engineering practices that support accuracy, reliability, and growth while collaborating closely with business stakeholders.
What You'll Do
Design, build, and maintain scalable data pipelines and ETL processes to support business analytics
Perform data manipulation, transformation, and cleansing to ensure accuracy and integrity
Develop and maintain database solutions using SQL
Implement and optimize data models and storage solutions in Snowflake
Leverage AWS services for data storage, processing, and analytics
Use Terraform to manage and deploy cloud resources as infrastructure-as-code
Orchestrate workflows and schedule pipelines using Apache Airflow
Work with dbt (Data Build Tool) to develop, test, and maintain modular data transformations
Create and maintain reports and dashboards in Looker
Apply AI and machine learning concepts to improve data workflows, automation, and insights generation
Use AI coding tools actively in daily development workflow to accelerate delivery
Collaborate with the team to continuously improve data engineering practices and processes
How You'll Succeed
You deliver reliable,



well-tested pipelines that scale with business growth
You proactively identify data quality issues and implement solutions before they impact stakeholders
You communicate technical concepts clearly and confidently in collaborative settings
You balance speed with quality, knowing when to optimize and when to ship
You share knowledge openly and help elevate team capabilities
Who You Are
Strong Python programming skills for data engineering tasks
Proficiency in data manipulation and transformation
Strong SQL skills for database management and querying
Hands-on production experience with Apache Airflow for workflow orchestration
Hands-on production experience with dbt for building scalable and maintainable data models
Proficiency with Terraform for infrastructure automation
Experience with AWS services for data engineering workloads
Proficiency in Snowflake including administration experience
Experience with Looker for reporting and dashboards
Active daily use of AI coding tools (Claude Code, GitHub Copilot, or similar) in development workflow
Exposure to AI concepts or tools applied to data workflows or analytics use cases
Strong understanding of data modeling principles and best practices
Excellent English communication skills.
vocal, extroverted, and confident sharing ideas in collaborative settings
Position Details
Remote: Fully-remote
Location: State of São Paulo, San José, Santo Domingo, Buenos Aires, Santiago, Bogota, Quito, Guatemala City, Tegucigalpa, Lima, Montevideo Department
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📌 Data Engineer (Buenos Aires)
🏢 Perform
📍 Buenos Aires