Senior Data Engineer
AirspaceSan Diego, CA - Hybrid Posted 26 March 2026
Job Description
Company Introduction:
Airspace
is a tech-enabled freight forwarder that’s redefining how the world’s most critical packages are delivered. Headquartered in Carlsbad, California, Airspace has employees who are based around the world. Our European headquarters is in Amsterdam, The Netherlands.
As a recognized leader in AI and machine learning, our team leverages data and patented technology to coordinate logistics across a global network of drivers and airlines. Our goal is to deliver those packages that are truly mission-critical in a way that is faster, more transparent, more secure, and more accountable than ever before. The items we deliver range from organs for transplant, to parts for critical machinery including grounded aircraft and highly sensitive components such as semiconductors.
Airspace has been rated one of
America’s best Startup Employers
, listed as one of
CNBC’s Disruptor 50
companies, and featured as an
Innovation and Disruption leader
by CBS News. Airspace has the support of leading investors such as Telstra Ventures, HarbourVest Partners, Defy Partners, DBL Partners, and Scale Ventures. To date the company has
raised more than $140m.
The company is growing rapidly and serving more places around the world than ever before. We are looking for passionate, motivated individuals who want to make an IMPACT every day to help us execute on our mission of reshaping the world of time-critical logistics.
About the Role
As Senior Data Engineer, you will be the owner of all data infrastructure and ETL processes at Airspace. You will be responsible for ensuring our data pipelines are performant, scalable, and robust — and that they support our business needs today and as we grow.
This role is not just about building great infrastructure — it’s about being a great teammate. We’re looking for someone who brings technical excellence and positive energy to the team, who can lead without ego, teach without condescension, and collaborate with humility and clarity.
You’ll be the technical thought leader for data engineering: advising on architectural decisions, executing high-impact refactors, and setting the roadmap for how data flows through our systems. This is a high-impact, high-autonomy role reporting directly to the Director of Data Science and AI, with the opportunity to shape the future of our data platform.
What You’ll Do
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
Be a technical leader and strategic architect
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
Continuously evaluate and recommend tools, frameworks, and methodologies that enhance platform capabilities and developer velocity
Level up our data function across the full lifecycle
Act as a trusted partner to stakeholders in Product, Data Science, and Infrastructure, helping shape technical roadmaps that align with business priorities
Identify and resolve systemic bottlenecks in our data workflows, and proactively implement process improvements
Mentor teammates and foster a collaborative, inclusive, and high-performing engineering culture
What We’re Looking For
Required Skills Experience
6+ years of experience in data engineering or backend infrastruct ... (truncated, view full listing at source)
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