Data Engineer LATAM

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.