Data Engineer LATAM

Description We are seeking an experienced Data Engineer. The ideal candidate is self-motivated, a multitasker, and a demonstrated team player. You will be responsible for designing, developing, managing, and maintaining our open-source data platform, including our Data-Lakehouse (S3, Apache Iceberg, and ClickHouse), ETL processes, and orchestration tool (Temporal Workflow).

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 and orchestrate workflows using Temporal.

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 (e.g., Temporal, Airflow, or similar).

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.

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