Please strictly adhere to the following resume naming convention: Please do not forge integration profiles as Palantir. Candidates must actually have experience with Palantir. Senior Forward Deployed Engineer (Delta) About the Role As a Senior Forward Deployed Engineer (Delta), you will serve as the technical leader at the intersection of Palantir Foundrys platform capabilities and DaVitas most complex, high-impact healthcare data and operational engagements. This role combines deep technical expertise in Palantir Foundry with strategic deployment leadership, driving transformational outcomes for DaVitas kidney care and healthcare operations. The Delta designation reflects a commitment to driving change and transformation you are the catalyst who bridges the gap between what the platform can do and what it should do for DaVitas unique operational context. You will be expected to be hands-on and an independent FDE owning , architecting enterprise-grade solutions, development, deployment, mentor as needed, and shape the technical strategy for critical engagements across DaVitas healthcare ecosystem. Key Responsibilities Technical Leadership & Architecture Design, build, and deploy end-to-end data integration pipelines using Palantir Foundry, including complex transforms, incremental pipelines, and multi-source data connectors Architect and maintain the Ontology layer defining object types, link types, action types, and interfaces that model customer domains with precision and scalability Develop and optimize Python, SQL, and Java transforms across distributed (PySpark) and lightweight (Pandas, Polars, DuckDB) compute engines Build and deploy TypeScriptPython Functions for server-side business logic, function-backed actions, and function-backed columns Create and configure Workshop applications, OSDK-based custom applications, and custom widgets to deliver operational front-ends Lead data governance implementation markings, permissions, restricted views, property security groups, and role-based access controls Design and deploy AIP-powered workflows, including AIP Logic, AIP Agents, evaluation suites, and retrieval-augmented generation (RAG) pipelines Deployment Strategy & Customer Engagement Serve as the primary technical point of contact for senior customer stakeholders, translating business problems into platform solutions Own deployment roadmaps end-to-end: scoping, architecture design, implementation, testing, and operationalization Drive adoption by delivering high-quality, production-grade solutions that users trust and rely on daily Navigate complex organizational dynamics, building relationships with executives, analysts, data engineers, and end users Identify expansion opportunities by deeply understanding the customers operational landscape and surfacing new use cases for the platform
Skills:
Team Leadership & Mentorship Lead and mentor a team of Forward Deployed Engineers, providing technical guidance, code reviews, and architecture direction Establish engineering best practices across the deployment: branching strategies (global and local), incremental pipeline design, testing, and CICD Conduct knowledge-sharing sessions and internal trainings on Foundry capabilities, new platform features, and deployment patterns Contribute to DaVitas internal engineering culture through tooling improvements, documentation, and cross-team collaboration Platform Mastery & Innovation Stay at the forefront of Foundry platform evolution including Pipeline Builder, Code Workspaces, Model Studio, OSDK, Cipher, and streaming capabilities Build and deploy machine learning models using Model Studio (no-code) and pro-code repositories for classification, regression, time series forecasting, and custom predictive modeling Leverage the full data lifecycle: Data Connection Sync Datasets Transforms Ontology Applications Actions Writeback Partner with Palantir product teams and DaVitas internal Palantir development team to provide field feedback and shape the future direction of the platform
Education:
Required Qualifications 5+ years of experience in software engineering, data engineering, or technical consulting with at least 2+ years on Palantir Foundry Strong proficiency in Python (PySpark, Pandas, Polars) and SQL experience with TypeScript is highly valued Deep understanding of the Foundry Ontology object types, link types, action types, interfaces, and functions Proven track record of designing and deploying production-grade data pipelines (batch and streaming) at enterprise scale Experience building Workshop applications andor OSDK-based applications (ReactTypeScript) Strong communication skills with the ability to engage both technical and non-technical stakeholders Preferred Qualifications Experience with Google Cloud Platform (Google Cloud Platform) Compute Engine, Cloud Functions, Cloud Storage, Dataflow, PubSub, and IAM Experience with Google BigQuery query optimization, partitioningclustering strategies, BigQuery ML, data warehousing patterns, and migration from legacy EDW platforms (e.g., Netezza, Teradata) Experience with AIP (AI Platform) AIP Logic, AIP Agents, evaluation suites, and LLM-powered functions Familiarity with machine learning workflows in
Foundry:
Model Studio, pro-code model authoring, batchlive inference Experience implementing data governance frameworks markings, ABAC, restricted views, Cipher for data protection, and HIPAA-compliant data handling Background in healthcare, kidney care, or clinical operations, revenue cycle optimizations a plus. Experience leading teams of 3+ engineers in forward-deployed settings Contributions to internal tooling, open-source projects, or platform evangelism Technical Skills Summary Category Technologies & Skills Languages Python, TypeScript, SQL, Java Data Engineering PySpark, Pandas, Polars, DuckDB, Pipeline Builder, Incremental Pipelines Cloud Platforms Google Cloud Platform (Google Cloud Platform), BigQuery, Cloud Storage, Dataflow, PubSub, Cloud Functions Ontology Object Types, Link Types, Action Types, Interfaces, Functions, OSDK Applications Workshop, OSDK (ReactTypeScriptPython), Custom Widgets
AI ML AIP
Logic, AIP Agents, Model Studio, LLM Functions, Evaluation Suites, BigQuery ML Data Governance Markings, Permissions, Restricted Views, Cipher, ABAC, HIPAA Compliance Infrastructure Data Connections, Connectors, Syncs (BatchStreamingCDC),
Schedules, Google Cloud Platform Networking Role Descriptions:
