Data Engineer Latam

Onebeat; Bogotá; In loco; COP 133.920.000 - 178.560.000; Tempo pieno

Descrizione del lavoro

Onebeat is seeking an experienced Data Engineer to design, develop, and maintain a scalable data platform, including a Data-Lakehouse, ETL processes, and Temporal workflows. You’ll collaborate with data scientists, analysts, and engineers to deliver reliable data solutions and governance across the stack.

The role emphasizes batch data processing with strong SQL, Python/Scala/Java coding, and cloud experience (AWS). Excellent communication and teamwork are essential for success.

Competenze

• 3+ years of experience as a Data Engineer or in a similar data infrastructure role.
• Strong proficiency in SQL and data modeling.
• Experience with data lake/lakehouse architectures (e.g., Apache Iceberg, S3, or similar).
• Experience with analytical/columnar databases (e.g., ClickHouse).
• Experience building and orchestrating ETL/ELT pipelines (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, multitasking, and team-oriented.
• Hands-on experience with Apache Spark.
• Proficient in written and spoken English.
• Note: focus on batch data processing; not real-time streaming.

Mansioni

• Develop a scalable data platform integrating multiple sources for easy access.
• Design and enhance data tools (orchestration, governance, Data-Lakehouse, BI).
• Ensure smooth operation of data systems for analysts, scientists, and engineers.
• Optimize data pipelines (ingestion, processing, output) in a microservices environment.
• Build, maintain, and monitor ETL/ELT processes and orchestrate workflows using Temporal.
• Troubleshoot and improve performance, scalability, and reliability of data infra (S3, Iceberg, ClickHouse).
• Collaborate cross-functionally with data scientists, analysts, and backend engineers.
• Implement and champion data quality, governance, and security best practices across the platform.

Conoscenze

SQL

Data modeling

Python

Scala/Java

Temporal

AWS

Batch processing

English

Git

Team player

Strumenti

Apache Spark

Apache Iceberg

ClickHouse

Data Lakehouse

Temporal Workflow

Descrizione del lavoro

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.