Data Engineer
- 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
- 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
- Startup experience
- Bachelor's Degree in Computer Engineering, Computer Science, or equivalent