Guidehouse

PalantirDataPipeline&MetadataLead

$149–248k McLean, Virginia, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Palantir Data Pipeline & Metadata Lead at Guidehouse. Skills: Palantir Foundry, Data pipelines, Metadata management, Data governance. Lead design of data pipelines. Lead development of data pipelines”

Industry & Context.

Eligibility Requirements

Up to 25% travel, Ability to Obtain Public Trust, U.S. Citizenship

What They're Looking For.

Must Have

Bachelor's degree, 8+ years experience, U.S. Citizenship required, Palantir Foundry expertise, Palantir AIP expertise, Experience leading Palantir implementations, Experience designing large-scale data pipelines, Experience integrating Palantir with Databricks, Expertise in metadata management, Expertise in data governance, Experience implementing data quality frameworks, Understanding of data lake architectures, Proficiency in Python, Proficiency in SQL, Experience designing AI/ML systems, Experience with document processing pipelines, Leadership skills, Communication skills, Experience managing cross-functional teams, Experience delivering in Agile environment

Nice to Have

Master's degree preferred, Experience growing Palantir federal capabilities, Experience designing AI-ready data architectures, Experience with enterprise ML platforms, Familiarity with OCR/ICR pipelines, Experience implementing data governance frameworks, Prior experience with federal agencies, Experience in consulting environment, Experience supporting training, Familiarity with graph-based data models, Relevant certifications

What You'll Do.

Lead design of data pipelines

Lead development of data pipelines

Lead governance of data pipelines

Lead design of metadata frameworks

Lead development of metadata frameworks

Lead governance of metadata frameworks

Serve as technical lead

Serve as functional lead

Define metadata standards

Enforce metadata standards

Define data dictionaries

Enforce data dictionaries

Oversee implementation of data pipelines

Establish data quality processes

Govern data quality processes

Establish validation processes

Govern validation processes

Establish exception handling processes

Govern exception handling processes

Ensure alignment with enterprise architecture

Ensure alignment with system-of-record requirements

Ensure alignment with integration patterns

Ensure pipelines support document-based ingestion

Enable AI-ready data foundations

Support semantic search

Support entity resolution

Support advanced analytics

Partner with data science teams

Partner with engineering teams

Drive data governance

Drive lifecycle management

Oversee integration across platforms

Provide technical direction

Provide quality oversight

Engage with senior stakeholders

Prioritize initiatives

Translate business needs

Oversee backlog prioritization

Oversee technical design reviews

Oversee iterative delivery

How You'll Work.

Team & Collaboration

Matrixed environment; Cross-functional teams; Agile delivery model

Communication Scope

Stakeholder engagement

Process & Methodology

Agile delivery

Full Job Description

**_Job Family_ :** Data Engineering & Architecture Consulting ** _Travel Required_ :** Up to 25% **_Clearance Required_ :** Ability to Obtain Public Trust ** _What You Will Do_ :** This role serves as a senior technical leader responsible for establishing and scaling the data pipeline and metadata foundation that enables enterprise analytics, AI-driven capabilities, and system integration. The ideal candidate combines deep, demonstrable Palantir (including AIP) expertise, strong data architecture and governance experience, and the ability to lead teams and grow capabilities in complex, regulated environments. **Roles & Responsibilities** * Lead the design, development, and governance of enterprise data pipelines and metadata frameworks within Palantir Foundry and integrated data platforms. * Serve as the technical and functional lead for data ingestion, transformation, and metadata management across structured and unstructured data sources. * Define and enforce metadata standards, data models, ontologies, and data dictionaries to enable scalable search, analytics, and cross-system integration. * Oversee implementation of end-to-end data pipelines, including ingestion, validation, transformation, and delivery into downstream platforms (e.g., Palantir, Databricks). * Establish and govern data quality, validation, and exception handling processes, ensuring completeness, accuracy, and traceability of data assets. * Ensure alignment of pipelines and metadata with enterprise architecture, system-of-record requirements, and integration patterns. * Ensure pipelines effectively support document-based ingestion workflows, including integration with OCR/ICR outputs and downstream metadata extraction processes. * Enable AI-ready data foundations, supporting downstream capabilities such as semantic search, entity resolution, and advanced analytics. * Partner with data science and engineering teams to ensure data pipelines and metadata support AI/ML use cases and analytical workf

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