Palantir Foundry Support Engineer-MHP 2553

Role Overview We are seeking an experienced Palantir Foundry Support Engineer to join Client’s Data Platform team. The selected engineer will be responsible for providing post-launch support, enhancements, and issue resolution for Client’s implementation of the Palantir Foundry platform. This role involves working closely with Client’s internal stakeholders to troubleshoot user issues, validate data accuracy, and deliver iterative improvements to ensure an optimal experience for users leveraging the Foundry environment. Key Responsibilities • Support day-to-day operations of Client’s Palantir Foundry platform. • Investigate and resolve user-reported issues such as: • Incorrect or missing data in visualizations or dashboards. • Data availability and synchronization problems. • Implement post-launch enhancements and user experience improvements. • Collaborate with Client’s data engineering and product teams to troubleshoot data flows and integrations. • Identify and fix bugs impacting system functionality, data pipelines, or UI components. • Participate in discussions around best practices for Foundry support and scalability. • Document issue resolutions and share learnings for future process improvements. Required Qualifications • 3+ years of experience in data engineering, analytics, or platform support roles. • Strong hands-on experience with Palantir Foundry, including: • Data pipelines, ontology, and operational layers. • Workflow debugging and deployment processes. • Foundry tools such as Code Workbooks, Contour, or Transform. • Proven ability to troubleshoot complex data and application issues. • Experience collaborating with business and technical teams to identify and resolve platform issues. • Excellent communication skills with the ability to explain technical findings to non-technical users. Preferred Skills • Experience with one or more data visualization / analytics tools: • AWS QuickSight (highest priority) • Qlik Sense / QlikView • Tableau • Experience in cloud environments such as AWS, Azure, or GCP. • Familiarity with SQL, Python, or Spark for data validation and transformation. • Exposure to Agile methodologies and fast-paced product environments.