Remote job
Senior Data Engineer (LATAM)
Job details
About this role
Role overview
Own the stabilization and improvement of a production data platform that consolidates dozens of sources in Snowflake. You’ll make data pipelines and reporting more dependable, reduce manual work, and help business teams make informed investment and operational decisions. The role combines hands-on engineering with technical judgment and close collaboration across a small, senior team.
Responsibilities
- Assess inherited pipelines and platform components, identify performance, cost, and data quality issues, and prioritize fixes. - Build and maintain ETL/ELT pipelines that integrate data from many sources. - Improve data models and reporting layers so metrics and business reporting have a reliable source of truth. - Automate manual data processes and improve how teams access timely information. - Review code, document design decisions, and explain technical tradeoffs to non-engineering partners. - Support analysis for transactions, leasing, valuation, fund and asset performance, and day-to-day operations.
Requirements
- At least five years of data engineering experience, including ownership of a production platform. - Practical Snowflake experience, including warehouse sizing and cost control, MERGE patterns, streams and tasks, and clustering. - Experience troubleshooting pipelines built by others, including slow queries, unexpected costs, and data quality failures. - Strong ETL/ELT and data integration skills across multiple sources. - Sound data modeling practices, including defining grain, organizing raw-to-mart layers, and handling corrections and late-arriving data. - Advanced SQL, including window functions and query performance tuning; experience with a transformation framework such as dbt and an orchestrator such as Airflow or Dagster.
Benefits and work setup
The team works in a distributed, self-managed environment that relies on proactive communication, clear documentation, and comfort with shifting priorities. The selection process includes a review of work, a take-home exercise, an engineering discussion, and a conversation about project collaboration and prioritization.