Full Stack Data Engineer - Internal Flight Data Applications

Pivotal is the leader in the emerging market of electric Vertical Takeoff and Landing (eVTOL) aircraft. We design, develop, and manufacture light eVTOL aircraft and are renowned for the BlackFly aircraft the world's first light eVTOL to fly manned missions and enter the consumer market.

Efficient, compact, and simple, Pivotal aircraft are designed for a wide range of consumer, public service, and defense applications. Our distinctive tilt-aircraft architecture and scalable platform have been flying for over 10 years. Last year we announced our next-generation aircraft, the Helix, which is rapidly progressing toward general release and scalable production in 2026.

Mobility is one of the most highly-valued areas of modern technology investments. This is the right company, in the right space, the right strategy, at the right time. If you are ready for adventure, we invite you to join our amazing team and grow with us.

About the Job

Flight data from across our aircraft fleet feeds a central data platform that engineering teams rely on to understand how the aircraft perform. Pivotal is seeking a Full Stack Data Engineer to build the internal applications that put that data directly in engineers' hands, so teams across the company can explore it and answer their own questions.

You will work across the whole stack — backend services over the data platform, web front ends that make large datasets explorable, dashboards, AI-assisted tooling that helps engineers interpret what they are looking at, and the packaging that puts analysis tools on an engineer's laptop. Your users sit down the hall, and requirements arrive as a conversation with someone who needs an answer rather than as a written spec, so this role is as much about understanding the question as it is about shipping the tool. It suits an engineer early in their career who wants ownership of real products and direct contact with the people building and flying the aircraft.

Responsibilities

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Internal applications: Build and maintain the internal web applications engineers use to work with flight data — flight record browsers, query interfaces, and analysis tools over the warehouse.

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Backend services: Develop Python services and HTTP APIs that query Athena and S3 and return results at interactive speed, including pagination and caching over large result sets.

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Front end: Build interfaces that make large telemetry datasets explorable — sortable tables, filters, and time-series plots — for engineers who are never going to write SQL.

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AI-assisted diagnosis: Build agent-based tooling over the data platform so engineers can ask questions in plain language and follow a symptom through to a root cause without hand-writing queries. Design these tools to return the underlying data and how it was derived, not just an answer, so an engineer can verify the result before acting on it.