Airspace is looking to solve the problem of inefficient and non-transparent logistics for time-critical packages by leveraging AI and machine learning. The Senior Data Engineer will be responsible for ensuring the data infrastructure and ETL processes are performant, scalable, and robust to support the company's growth and mission.
Requirements
- 6+ years of experience in data engineering or backend infrastructure roles
- Expert level Python engineering skills
- Thorough knowledge and understanding of Airflow (familiarity with Astronomer or Google Cloud Composer is a plus)
- Experience managing and optimizing data infrastructure built on Snowflake (preferred) or BigQuery, including warehouse design, performance tuning, and cost efficiency
- Familiarity with dbt core, including how it fits into modern data pipelines and transformation layers
- Solid understanding of SQL (especially in the context of large-scale warehouse environments)
- Proficiency in Git, version control, and collaborative development workflows
Responsibilities
- Own and evolve our data infrastructure and pipelines
- Design, build, and maintain reliable ETL pipelines that ingest data from internal application postgres databases and external SaaS platforms (e.g. Salesforce, Twilio, Zendesk)
- Manage and scale our orchestration layer built in Airflow
- Ensure reliability, consistency, and performance across our data systems through strong engineering practices and operational discipline
- Oversee and optimize how data flows into and through our warehouse layer (Snowflake), ensuring transformations (via dbt) integrate cleanly into upstream and downstream systems
- Set a high bar for technical excellence, promoting clean architecture, code quality, and maintainability through thoughtful design, hands-on coding, and code reviews
- Drive architectural improvements and lead system-level refactors to improve performance, scalability, and efficiency
Other
- Be a technical leader and strategic architect
- Act as a trusted partner to stakeholders in Product, Data Science, and Infrastructure, helping shape technical roadmaps that align with business priorities
- Collaborative and approachable
- Feedback-oriented
- Bias for action
