Data Engineer

  • Closed
  • US Company | Medium ( employees)
  • LATAM (100% remote)
  • 5+ years
  • Short-term · 6 months · 40h/week
  • Hospitality
  • Full Remote

Required skills

  • AWS Glue
  • Terraform
  • Python
  • CI/CD
  • AWS
  • ETL
  • AWS S3
  • Iceberg

Requirements

Must-haves

  • 5+ years of data engineering experience
  • Experience building end-to-end production data pipelines across landing, transformation, and analytics layers (e.g. S3, AWS Glue, Iceberg)
  • Experience with AWS-native ETL development (e.g. AWS Glue, S3, Iceberg)
  • Experience provisioning and managing pipeline infrastructure with Terraform (e.g. Glue job configuration, Iceberg warehouse paths, per-environment asset buckets)
  • Experience packaging and distributing shared Python logic as .whl files via --extra-py-files in Glue
  • Experience with CI/CD pipelines for data infrastructure and code artifacts (e.g. GitHub Actions)
  • Proficiency with system instrumentation (e.g. alerting, monitoring, data lineage, validation frameworks)
  • Strong communication skills in both spoken and written English

Nice-to-haves

  • Startup experience
  • Bachelor's Degree in Computer Engineering, Computer Science, or equivalent

What you will work on

  • This is a full-time role (40 hours/week) for a 6-month contract
  • Build and maintain an hourly gold-layer pipeline that reads a per-client Iceberg metric registry (materialized from YAML via CI) and computes base sums, compounds, and ratios, storing additive numerator/denominator pairs alongside an audit-only daily ratio
  • Maintain and evolve a long-format fact table (reporting_metric_fact) with OK/ERR status marking, completeness reporting, cascade reprocessing on variant changes, and atomic commits for consistent downstream reads