Related skills
aws etl gcp dbt airflow📋 Description
- Design, build, and maintain scalable data pipelines and infrastructure
- Develop batch and streaming systems for large-scale data
- Own core data platform components (warehouse, lake, orchestration, tooling)
- Implement data modeling, transformation, and versioning frameworks
- Ensure data quality, observability, and reliability across pipelines
- Partner with data scientists and engineers to productionize ML workflows
🎯 Requirements
- 3–7+ years in data infrastructure or platform engineering
- Real-time and batch data processing (Spark, Kafka, etc.)
- Modern data tooling: dbt, Airflow, etc.
- Data modeling, ETL/ELT, reverse ETL, and orchestration
- Design for scalability, reliability, and observability
- Cloud platforms (AWS/GCP) and storage systems
🎁 Benefits
- Equity
- Health, dental, vision coverage
- Flexible PTO
- Opportunity to join early and shape the foundation
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