Configure and maintain reliable data feeds from source systems into a data platform.
Set up and manage data connections, pipelines, and synchronization between source systems and data assets.
Design and implement data transformations and derived datasets using the platform’s code based and code less tooling (including Spark-based transforms and Contour).
Model operational data, including defining objects, relationships, and actions that reflect real-world entities and workflows.
Build and configure applications (e.g., Workshop, Slate, Object Explorer, and other Ontology-backed apps) to answer concrete operational questions.
Leverage AI-powered capabilities to automate workflows, surface insights, and support user decision-making.
Monitor build pipelines and Ontology-backed applications, investigate failures or degraded performance, and drive fixes across the stack.
Work iteratively with subject matter experts to prototype, test, and refine data-driven applications and workflows.
Collaborate with central platform/product teams to troubleshoot complex issues, understand platform behavior, and contribute field feedback into product evolution.

Active Secret security clearance.
Strong engineering or quantitative background in fields such as Computer Science, Software Engineering, Mathematics, Physics, or Data Science (or equivalent practical experience).
Proficiency in programming or scripting languages commonly used within the platform, such as Python (including PySpark, Pandas) and SQL.
Understanding of data modeling and object-based / ontology-driven design, including representing operational entities and workflows as objects, relationships, and actions.
Familiarity with distributed data processing frameworks (Spark or similar) and version-controlled development practices.
Experience working with AI-enabled data or decision support tools (agents, copilots, or similar).
Ability to collaborate effectively with technical and non-technical stakeholders, including field operators and mission owners.
Comfort operating in rapidly changing environments with evolving requirements and frequent iteration with end users.
Demonstrated ability to learn new platform features quickly, work independently, and make sound technical decisions with limited supervision.
Proven track record of clear customer communication, including gathering requirements, providing execution updates, and troubleshooting in high-stakes environments.

Field Data Platform Engineer

Key skills