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. Originally posted on Himalayas