Senior Data Engineer (SaaS and on-premise hybrid environment)

Are you passionate about building scalable data platforms and enabling data-driven decision-making? We're looking for a Senior Data Engineer to join our team and help design, build, and optimize modern data solutions that power analytics and machine learning initiatives.

As part of this role, you'll work in a SaaS and on-premise hybrid environment, developing reliable data pipelines and contributing to the evolution of our Elastic Hierarchy framework.

Remote – LATAM

Full-Time

• →Design, develop, and maintain scalable ETL/ELT data pipelines using Python.
• →Build and optimize data workflows using DBT and orchestration tools such as Airflow, Prefect, or Dagster.
• →Process and integrate data from multiple sources and formats, including JSON, CSV, and XML.
• →Maintain and enhance the Elastic Hierarchy data framework.
• →Ensure data quality, governance, and security across the platform.
• →Collaborate with analytics, machine learning, and product teams to deliver business-ready datasets.
• →Support data operations across SaaS and on-premise environments.

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
• Strong Python development experience.
• Hands-on experience with AWS services, including S3, Glue, Lambda, EMR, EC2, Redshift, and RDS.
• Experience with Snowflake, MongoDB, and PostgreSQL.
• Experience with DBT and at least one orchestration tool (Airflow, Prefect, or Dagster).
• Knowledge of data mapping, attribution, and reconciliation processes.
• Experience working with hybrid and on-premise deployment environments.
• Strong English communication skills.