• 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.