Seed Health is looking for a Data Engineer to architect and steward their data infrastructure, ensuring data quality, accessibility, and performance to empower data-driven decisions across the organization.
Requirements
- Expert-level knowledge of modern data stack (Snowflake, dbt, Fivetran, Airflow)
- Experience building custom ETL/ELT pipelines and API integrations
- Proven ability to design data warehouse architectures and optimize query performance
- Deep knowledge of SQL, Python, and data modeling best practices
- Snowflake and SQL: Query optimization, warehouse management, access controls
- Modern data stack: Fivetran, dbt, Airflow, and cloud data warehouses
- Python: ETL/ELT scripting and API integrations
Responsibilities
- Build and maintain production-ready data pipelines that power business intelligence, experimentation, and scientific discovery
- Manage and optimize our Snowflake data warehouse—monitoring performance, costs, and query efficiency
- Make technical architectural decisions about data modeling, warehouse design, and pipeline orchestration
- Drive reliability and observability across the data stack through monitoring, alerting, and documentation
- Partner with Analytics and Reporting team to ensure the infrastructure serves both technical and business needs
- Implement robust data quality testing, validation, and monitoring frameworks
- Build custom ETL/ELT solutions for data sources not supported by out-of-the-box connectors
Other
- 4+ years of professional data engineering experience
- Strong collaboration and communication skills across technical and non-technical teams
- Translate stakeholder data requirements into technical solutions
- Collaborate with Analytics, Product, and Marketing teams on feasibility and technical guidance
- Participate in data architecture discussions with Engineering leadership
