Job description

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. Pivotal is seeking a Data Engineer to build and operate the flight data warehouse — the system of record for telemetry off every aircraft in the fleet. Flight logs land continuously from customer and test aircraft; you will turn them into curated datasets, automated fleet health alerts, and dashboards that the firmware, GNC, battery, flight operations, and MRO teams rely on to make airworthiness and design decisions. This is a small team building production infrastructure, so you will own pipelines end to end: the data model, the services that run on it, the infrastructure as code that deploys them, and the monitoring that tells us when they break. Responsibilities Pipeline development: Build and maintain the ingest and transformation pipelines that land aircraft telemetry from S3 into the flight data warehouse (AWS Glue, Athena), including schema evolution as firmware logging changes. Data modeling: Design and maintain curated marts — flight runs, component flight hours, vehicle modes, battery flight features — in SQL, with clear grain, documented lineage, and idempotent incremental refresh. Fleet alerting services: Develop and operate the Python services that evaluate flight-by-flight health checks and deliver alerts to engineering and customer-facing channels via SNS and Slack. Data quality: Own the automated quality gates — mart freshness, source-to-mart reconciliation, and watermark integrity — and block deploys that would publish incorrect fleet data. Analytics enablement: Build the dashboards and query interfaces engineering teams use to monitor the fleet, and convert repeated one-off analyses into supported datasets. Collaboration: Work directly with firmware, GNC, battery, systems engineering, flight operations, and MRO to define what gets logged, what gets alerted on, and what “good” looks like for each signal. Qualifications Bachelor’s degree in Computer Science, Computer/Electrical Engineering, or a related technical discipline 3+ years of professional data engineering experience building and operating production pipelines Strong SQL, including window functions and query tuning on a distributed, columnar engine (Athena/Trino/Presto, Spark, Snowflake, or BigQuery) Proficient in Python for production services — not just notebooks: packaging, dependency management, unit tests, and code review Hands-on experience with the AWS data stack: S3, Glue, Athena, Lambda, SNS, CloudWatch, and IAM Dimensional modeling and warehouse design, including partitioning strategy for large tables Excellent analytical and written communication skills, with the ability to work across multidisciplinary teams Preferred Qualifications 5+ years of relevant data engineering experience, including ownership of an on-call or operationally critical data system Infrastructure as code with Terraform, and building deployment pipelines in GitLab CI or equivalent Transformation frameworks such as dbt, and data quality/testing frameworks High-volume time-series or sensor telemetry, and observability tooling (Grafana, CloudWatch, or similar), including alert design that avoids alarm fatigue Familiarity/experience with one or more of the following Aerospace, automotive, or robotics telemetry and flight/vehicle test data Embedded logging formats and decoding raw device logs (CAN, serial, or proprietary binary packet formats) FAA aircraft certification or continued airworthiness processes Interest in RC planes, quadcopters, or aviation Applicants must be eligible for employment in the United States and willing to work onsite at our HQ office in Palo Alto, CA. Pivotal offers a comprehensive benefits package, including medical, dental, vision, and 401k plans. Pivotal is an Equal Opportunity Employer. Pivotal does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.

Requirements

Must-haves

Data modeling: Design and maintain curated marts — flight runs, component flight hours, vehicle modes, battery flight features — in SQL, with clear grain, documented lineage, and idempotent incremental refresh.
Fleet alerting services: Develop and operate the Python services that evaluate flight-by-flight health checks and deliver alerts to engineering and customer-facing channels via SNS and Slack.
Data quality: Own the automated quality gates — mart freshness, source-to-mart reconciliation, and watermark integrity — and block deploys that would publish incorrect fleet data.
Analytics enablement: Build the dashboards and query interfaces engineering teams use to monitor the fleet, and convert repeated one-off analyses into supported datasets.
Collaboration: Work directly with firmware, GNC, battery, systems engineering, flight operations, and MRO to define what gets logged, what gets alerted on, and what “good” looks like for each signal.
Bachelor’s degree in Computer Science, Computer/Electrical Engineering, or a related technical discipline
3+ years of professional data engineering experience building and operating production pipelines
Strong SQL, including window functions and query tuning on a distributed, columnar engine (Athena/Trino/Presto, Spark, Snowflake, or BigQuery)
Proficient in Python for production services — not just notebooks: packaging, dependency management, unit tests, and code review
Hands-on experience with the AWS data stack: S3, Glue, Athena, Lambda, SNS, CloudWatch, and IAM
Dimensional modeling and warehouse design, including partitioning strategy for large tables
Excellent analytical and written communication skills, with the ability to work across multidisciplinary teams
5+ years of relevant data engineering experience, including ownership of an on-call or operationally critical data system

Nice-to-haves

Infrastructure as code with Terraform, and building deployment pipelines in GitLab CI or equivalent
Transformation frameworks such as dbt, and data quality/testing frameworks
High-volume time-series or sensor telemetry, and observability tooling (Grafana, CloudWatch, or similar), including alert design that avoids alarm fatigue
Familiarity/experience with one or more of the following
Aerospace, automotive, or robotics telemetry and flight/vehicle test data
Embedded logging formats and decoding raw device logs (CAN, serial, or proprietary binary packet formats)
FAA aircraft certification or continued airworthiness processes
Interest in RC planes, quadcopters, or aviation
Applicants must be eligible for employment in the United States and willing to work onsite at our HQ office in Palo Alto, CA.

Application prep

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Keywords to mirror

awssqlpython

Platform: lever
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k