Foundry Engineer I: Data Pipelines & Workflows

Guidehouse; Huntsville (AL); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Competitive benefits package

Job summary

Guidehouse is seeking a data engineering specialist in Huntsville to design, develop, and maintain Palantir Foundry-based solutions. You will build scalable data pipelines, architect ontology models, and create user-facing applications using Foundry Workshops to support operational reporting, AI, and decision support.

The role requires collaboration with engineers, data scientists, and stakeholders to translate requirements into robust technical implementations, with emphasis on data governance,

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or STEM related field; in lieu of degree FOUR (4) additional years of experience is required
• TWO (2) or more years of experience developing solutions using Palantir Foundry, including data pipelines, transformations, data products, and application development.
• Experience developing Foundry Workshops and operational applications.
• Experience designing and implementing Ontology models supporting operational or analytical workflows.
• Experience with SQL and Python (particularly PySpark)
• Experience integrating structured and unstructured data from multiple enterprise data sources.
• Experience implementing data quality, validation, testing, and governance processes.
• Experience working with cloud platforms (Azure, AWS, Google cloud services) and modern enterprise data architectures.
• Familiarity with Agile software development methodologies and DevSecOps best practices.

Responsibilities

• Design, develop, configure, and maintain data integration, analytics, and operational solutions using Palantir Foundry and related enterprise data platforms.
• Build and maintain scalable data pipelines, transformations, and reusable data products supporting operational reporting, advanced analytics, AI, and decision support.
• Develop and maintain Palantir Ontology models, business objects, relationships, actions, and workflows that support operational and analytical use cases.
• Design and develop user-facing applications using Foundry Workshops and other Palantir application development capabilities.
• Integrate data from cloud platforms, enterprise applications, APIs, databases, and external data sources using scalable and secure integration patterns.
• Develop and optimize solutions using Python, SQL, and other modern programming languages for large-scale data processing and analytics.
• Implement data quality, validation, metadata management, lineage, and governance practices to ensure trusted, reusable, and well-documented data assets.
• Collaborate with data engineers, architects, data scientists, analysts, product owners, and business stakeholders to translate mission and business requirements into scalable technical solutions.
• Support Agile software development activities including sprint planning, backlog refinement, testing, deployment, troubleshooting, and continuous improvement.
• Prepare technical documentation including system diagrams, data flow diagrams, solution documentation, standard operating procedures, and implementation guides.
• Support technical modernization initiatives involving cloud platforms, enterprise data ecosystems, and AI-enabled analytics solutions.

Skills

Palantir Foundry

PySpark

SQL

Python

Cloud platforms

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or STEM related field

Tools

Foundry Workshops

Ontology models

Databricks

Azure Data Factory

Azure Data Lake

Microsoft Fabric

Job description

Guidehouse is seeking a data engineering specialist in Huntsville to design, develop, and maintain Palantir Foundry-based solutions. You will build scalable data pipelines, architect ontology models, and create user-facing applications using Foundry Workshops to support operational reporting, AI, and decision support.

The role requires collaboration with engineers, data scientists, and stakeholders to translate requirements into robust technical implementations, with emphasis on data governance,