Data Engineer
Summary
Build and maintain scalable data pipelines using Snowflake, AWS, Airflow, and dbt to turn raw data into insights and AI-powered improvements for analytics.
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
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Design, build, and maintain scalable data pipelines and ETL processes to support business analytics
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Perform data manipulation, transformation, and cleansing to ensure accuracy and integrity
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Develop and maintain database solutions using SQL
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Implement and optimize data models and storage solutions in Snowflake
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Leverage AWS services for data storage, processing, and analytics
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Use Terraform to manage and deploy cloud resources as infrastructure-as-code
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Orchestrate workflows and schedule pipelines using Apache Airflow
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Work with dbt (Data Build Tool) to develop, test, and maintain modular data transformations
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Create and maintain reports and dashboards in Looker
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Apply AI and machine learning concepts to improve data workflows, automation, and insights generation
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Use AI coding tools actively in daily development workflow to accelerate delivery
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Collaborate with the team to continuously improve data engineering practices and processes
How You'll Succeed
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You deliver reliable, well-tested pipelines that scale with business growth
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You proactively identify data quality issues and implement solutions before they impact stakeholders
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You communicate technical concepts clearly and confidently in collaborative settings
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You balance speed with quality, knowing when to optimize and when to ship
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You share knowledge openly and help elevate team capabilities
Who You Are
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Strong Python programming skills for data engineering tasks
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Proficiency in data manipulation and transformation
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Strong SQL skills for database management and querying
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Hands-on production experience with Apache Airflow for workflow orchestration
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Hands-on production experience with dbt for building scalable and maintainable data models
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Proficiency with Terraform for infrastructure automation
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Experience with AWS services for data engineering workloads
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Proficiency in Snowflake including administration experience
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Experience with Looker for reporting and dashboards
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Active daily use of AI coding tools (Claude Code, GitHub Copilot, or similar) in development workflow
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Exposure to AI concepts or tools applied to data workflows or analytics use cases
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Strong understanding of data modeling principles and best practices
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Excellent English communication skills. vocal, extroverted, and confident sharing ideas in collaborative settings
Position Details
- Remote: Fully-remote
- Location: Latin America
Your partner for AI, consulting, software development, and nearshore staffing.
As published by greenhouse
First Name, Last Name, Email, Phone, Resume/CV, Cover Letter, Location
- Preferred First Name optional
- LinkedIn Profile optional
- Website optional
- Do you have professional experience building data pipelines or ETL processes? choose one
- Have you used Python for data engineering or data transformation work? choose one
- Are you proficient in writing SQL for querying and managing databases? choose one
- Do you have hands-on experience working with Snowflake in a production environment? choose one
- Do you have hands-on experience using DBT (Data Build Tool) for building or managing data transformations in production environments? choose one
- Describe a data pipeline or analytics system you worked on. Explain what data it handled and your role in building or maintaining it. (Video Required)