Senior Data Engineer

📋 Description Architect for scale: define blueprints for high-scale data systems. Build the backbone: engineer robust ETL/ELT pipelines with Beam and Snowpark. Orchestrate workflows: build pipelines with Airflow, Google Workflows, Snowflake Tasks. Optimize storage: tune cloud storage across BigQuery, Snowflake, PostgreSQL, GCS. Own data quality: implement validation, tests, CI/CD, monitoring. Technical leadership: drive design discussions and mentoring. 🎯 Requirements Bachelor's or Master's degree in Computer Engineering, Software Engineering, Computer Science, or an equivalent technical field. 5+ years in Data Engineering with production data systems at scale. Deep ETL/ELT, data modeling, partitioning, idempotent pipelines, cost-aware storage. Cloud Expertise: production data workloads in the cloud (GCP preferred). Coding Fundamentals: advanced Python and SQL; modular, maintainable code for heavy data processing. Engineering Rigor: automated pipeline testing, CI, documentation, and observability. 🎁 Benefits Course Reimbursement Program for ongoing learning. Open and transparent communication including All Hands meetings with CEO. Ironwood Digital Learning Academy. Mental health support with Inkblot for virtual counseling. Flexible work environment and Summer Hours. 17 paid days off plus birthday day.