Senior Data Engineer

Role overview

Design and operate scalable data systems that make complex information reliable and useful for analytics and machine learning. The work spans batch and streaming pipelines, cloud data infrastructure, and collaboration with distributed engineering and data teams.

Responsibilities

- Build and maintain batch and real-time pipelines that ingest and process large, varied datasets. - Develop ETL/ELT workflows with Python and SQL across Azure or Google Cloud environments. - Improve automation, query performance, data freshness, scalability, and fault tolerance. - Create data tools, marts, and feature stores to support analytics, business intelligence, and model development. - Investigate pipeline issues, coordinate dependencies, and support sound data governance with cross-functional partners.

Requirements

- At least four years of professional data engineering experience, including data modeling, metadata management, and workload orchestration. - Advanced Python and complex SQL skills, plus production experience with Databricks. - Experience with Apache Spark and cloud data services such as Azure Data Factory, Azure Synapse, or Google BigQuery. - Track record building both batch and streaming pipelines for semi-structured or unstructured data at scale. - Advanced English proficiency (B2+/C1) and strong communication skills for technical work with North American teams; availability aligned with U.S. East or West Coast business hours.

Benefits and work setup

- Contractor engagement, fully remote within Latin America, with compensation in U.S. dollars. - Paid time off and holidays, plus assistance with health insurance. - Work with U.S.-based teams on varied projects; professional development resources and technical training are available.