Senior Data Engineer – AI Data Platform – ID #360

Werben HR LLC; Argentina; A distancia; ARS 135.820.000 - 196.185.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Fully remote

Descripción de la vacante

Werben HR in LATAM is seeking a Senior Data Engineer to design, build, and operate production-grade data platforms. You will own end-to-end data pipelines, work with Snowflake, dbt and Apache Airflow, and optimize for performance and cost.

This fully remote role emphasizes reliability, data quality, and scalable infrastructure within large data warehouses and cross-functional teams.

Formación

• 5+ years of professional experience as a Data Engineer or in a closely related role.
• Strong hands-on experience working with Snowflake in production environments.
• Advanced knowledge of Snowflake query profiling, performance tuning, clustering, warehouse sizing, and cost optimization.
• Solid experience with dbt, including: Data modeling, Incremental models, Materializations, Testing, Documentation.
• Strong experience developing, maintaining, and refactoring Apache Airflow pipelines.
• Advanced knowledge of Python and SQL.
• Proven experience working with large-scale data warehouses and production data platforms.
• Experience with data deduplication, consolidation, and safe warehouse refactoring.
• Strong understanding of data quality, reliability, and data integrity principles.
• Experience troubleshooting and resolving complex issues in production environments.
• Ability to take end-to-end ownership of technical solutions and deliver complex initiatives independently.
• Strong analytical and problem-solving skills.
• Upper-Intermediate to Advanced English proficiency (B2+/C1)

Responsabilidades

• Design, develop, maintain, and optimize data pipelines and data warehouse solutions.
• Develop and refactor Apache Airflow DAGs and data pipelines.
• Build and maintain scalable data models using dbt.
• Develop efficient and maintainable Python and SQL solutions.
• Optimize Snowflake workloads through query performance tuning, clustering strategies, warehouse sizing, and cost optimization.
• Analyze query execution and identify opportunities to improve performance and resource utilization.
• Perform safe deduplication, consolidation, and refactoring of production data warehouses.
• Troubleshoot complex data platform issues and ensure reliable production operations.
• Ensure data pipelines and transformations meet established standards for quality, consistency, and reliability.
• Take ownership of technical solutions from design and implementation through production deployment and troubleshooting.
• Collaborate with other engineering and technical stakeholders to improve the overall data platform.
• Contribute to the continuous evolution, scalability, and efficiency of the data infrastructure.

Conocimientos

Snowflake

dbt

Apache Airflow

Python

SQL

Data Pipelines

Descripción del empleo

#SeniorDataEngineer #Snowflake #DBT #ApacheAirflow #Python #SQL #DataEngineering #DataPlatform #DataWarehouse #DataPipelines

10 August, 2026

LATAM

Location: Remote LATAM
Employment Type: Full-time

We are looking for a Senior Data Engineer with strong hands‑on experience working with production‑grade data platforms and high‑scale environments.

The ideal candidate has deep expertise in Snowflake, dbt, Apache Airflow, Python, and SQL, combined with a strong understanding of data warehouse architecture, performance optimization, and production troubleshooting.

You will be responsible for designing, improving, and maintaining reliable data pipelines and warehouse solutions. This role requires someone who can take end-to-end ownership, independently troubleshoot complex production issues, and safely refactor existing data infrastructure without compromising data integrity or system reliability.

The position is particularly well suited for an engineer who enjoys working on complex data environments, optimizing performance and costs, and continuously improving the quality and scalability of data platforms.

Requirements

• 5+ years of professional experience as a Data Engineer or in a closely related role.
• Strong hands‑on experience working with Snowflake in production environments.
• Advanced knowledge of Snowflake query profiling, performance tuning, clustering, warehouse sizing, and cost optimization.
• Solid experience with dbt, including:
  • Data modeling
  • Incremental models
  • Materializations
  • Testing
  • Documentation
• Strong experience developing, maintaining, and refactoring Apache Airflow pipelines.
• Advanced knowledge of Python and SQL.
• Proven experience working with large‑scale data warehouses and production data platforms.
• Experience with data deduplication, consolidation, and safe warehouse refactoring.
• Strong understanding of data quality, reliability, and data integrity principles.
• Experience troubleshooting and resolving complex issues in production environments.
• Ability to take end-to-end ownership of technical solutions and deliver complex initiatives independently.
• Strong analytical and problem‑solving skills.
• Upper‑Intermediate to Advanced English proficiency (B2+/C1).

Responsibilities

• Design, develop, maintain, and optimize data pipelines and data warehouse solutions.
• Develop and refactor Apache Airflow DAGs and data pipelines.
• Build and maintain scalable data models using dbt.
• Develop efficient and maintainable Python and SQL solutions.
• Optimize Snowflake workloads through query performance tuning, clustering strategies, warehouse sizing, and cost optimization.
• Analyze query execution and identify opportunities to improve performance and resource utilization.
• Perform safe deduplication, consolidation, and refactoring of production data warehouses.
• Troubleshoot complex data platform issues and ensure reliable production operations.
• Ensure data pipelines and transformations meet established standards for quality, consistency, and reliability.
• Take ownership of technical solutions from design and implementation through production deployment and troubleshooting.
• Collaborate with other engineering and technical stakeholders to improve the overall data platform.
• Contribute to the continuous evolution, scalability, and efficiency of the data infrastructure.

What We Offer

• Fully remote work environment.
• Opportunity to work on a modern, high‑scale data platform.
• Exposure to AI and data‑driven technologies.
• Collaboration with distributed, international engineering teams.
• A challenging technical environment focused on scalability, performance, and continuous improvement.
• Opportunity to take significant technical ownership over complex data engineering initiatives.

Keywords

Snowflake, dbt, Apache Airflow, Python, SQL, Data Engineering, Data Warehouse, Data Platform, ETL, ELT, Data Pipelines, Query Optimization, Data Modeling, Cloud Data Platform.