Data Engineer LATAM

We are seeking an experienced Data Engineer. The ideal candidate is self-motivated, can multitask, and is a proven team player. You will design, develop, manage, and maintain our open-source data platform, including our Data Lakehouse (S3, Apache Iceberg, and ClickHouse), ETL processes, and orchestration.

What You Will Do

● Develop a scalable data platform integrating multiple sources for easy access.

● Design and enhance data tools (orchestration, governance, data lakehouse, BI, etc.).

● Ensure smooth operation of data systems for analysts, scientists, and engineers.

● Optimize data pipelines (ingestion, processing, and output) in a microservices environment.

● Build, maintain, and monitor ETL/ELT processes .

● Troubleshoot and improve the performance, scalability, and reliability of the data infrastructure (S3, Apache Iceberg, ClickHouse).

● Collaborate cross-functionally with data scientists, analysts, and backend engineers to understand data needs and deliver solutions.

● Implement and champion data quality, governance, and security best practices across the platform.

Requirements

● 3+ years of experience as a Data Engineer or in a similar data infrastructure role.

● Strong proficiency in SQL and hands-on experience with data modeling.

● Experience with data lake/lakehouse architectures (e.g., Apache Iceberg, S3, or similar).

● Experience with analytical / columnar databases (e.g., ClickHouse or similar).

● Experience building and orchestrating ETL/ELT pipelines .

● Strong programming skills in Python and/or Scala/Java.

● Experience working within a microservices architecture and cloud environments (AWS preferred).

● Self-motivated, strong multitasking skills, and a demonstrated team player.

● Excellent communication skills and the ability to work both independently and collaboratively.

● Hands-on experience with Apache Spark (or similar technologies) for large-scale data processing.

● Professional proficiency in written and spoken English.

● Note: this role is focused on batch data processing (not real-time streaming).

Nice to Have

● Experience working with and contributing to open-source data platforms and tools.

● Familiarity with BI and visualization tools (e.g., Superset, Looker, Tableau, Metabase, or similar).

● Experience with containerization and orchestration (Docker, Kubernetes).

● Experience with infrastructure-as-code and CI/CD practices.

● Experience with AWS EMR and running Apache Spark workloads in a cloud environment.

● Experience leveraging AI-assisted development tools (e.g., GitHub Copilot, Cursor, or similar) to boost engineering productivity.