Staff Software Engineer

Job Overview:
This role is a senior technical leadership position focused on architecting and scaling large-scale data systems and pipelines that support biosecurity and environmental monitoring use cases. The engineer will design and evolve backend data infrastructure across cloud data warehouses, ETL and ELT pipelines, and analytics systems. The ideal candidate will bring deep expertise in data engineering, cloud platforms, and distributed systems to build reliable, high-throughput data products. This role also involves collaborating with cross-functional teams to transform complex biological and environmental data into actionable insights.

Job Responsibilities:

• Lead the architecture, design, and implementation of scalable data warehouses, data marts, and ETL and ELT pipelines in cloud environments
• Build and optimize high-throughput data pipelines supporting structured and unstructured data from diverse biological and environmental sources
• Establish and enforce best practices for data modeling using dbt, including testing, documentation, and semantic consistency
• Own data governance initiatives to ensure data quality, integrity, accessibility, and consistency across systems
• Design and develop high-performance backend APIs and microservices in Python to support data access and integration
• Architect and manage production data workflows using orchestration tools such as Airflow or Dagster
• Improve cloud infrastructure and deployment patterns using AWS, Kubernetes, Docker, and infrastructure as code tools such as Terraform
• Implement observability, monitoring, and alerting solutions to ensure system reliability and performance
• Identify and resolve performance bottlenecks in data systems, optimizing for cost, speed, and scalability
• Partner with cross-functional stakeholders including product, science, and analytics teams to deliver production-grade data products

Qualifications:

• 10+ years of experience in data engineering or software engineering with a focus on large-scale production systems
• Strong expertise in SQL, including complex transformations and performance optimization
• Expert-level Python development experience, including building ETL frameworks and APIs using tools such as FastAPI or Flask
• Hands-on experience with dbt for data modeling, testing, and transformation workflows
• Experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift
• Strong background in workflow orchestration tools such as Airflow or Dagster
• Experience with AWS services including S3, IAM, and cloud security configurations
• Strong understanding of system design, CI/CD, Docker, and infrastructure as code practices such as Terraform
• Excellent communication skills with experience collaborating across technical and non-technical teams