Foundry Engineer I: Build Data Pipelines & Apps

Guidehouse; Houston (TX); On-site; USD 130,000 - 170,000; Full time

Benefits offered by this job

Medical Insurance

401(k) Retirement Plan

Tuition Reimbursement

Paid Holidays

Transit Benefits

Job summary

Guidehouse is seeking a Data Engineer to design, develop, and maintain Palantir Foundry-based data integration and analytics solutions. You will build scalable data pipelines, develop ontology models, and create user-facing applications using Foundry Workshops to support operational reporting and advanced analytics.

The role requires experience with SQL, Python, and cloud platforms, and involves collaboration with engineers, data scientists, and business stakeholders.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, Mathematics, or STEM field; in lieu of degree four additional years of experience.
• Two 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 (especially PySpark).
• Experience integrating structured and unstructured data from multiple enterprise data sources.
• Experience implementing data quality, validation, governance processes.
• Experience with cloud platforms (Azure, AWS, Google cloud services) and modern enterprise data architectures.
• Familiarity with Agile software development methodologies and DevSecOps 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.
• Ability to obtain and maintain a Public Trust or higher federal security clearance, as required.

Skills

Analytical skills

Communication

Education

Bachelor's degree or equivalent experience

Tools

Palantir Foundry

Palantir Ontology

Foundry Workshops

Python

SQL

PySpark

Azure

AWS

Databricks

Apache Spark

Job description

Guidehouse is seeking a Data Engineer to design, develop, and maintain Palantir Foundry-based data integration and analytics solutions. You will build scalable data pipelines, develop ontology models, and create user-facing applications using Foundry Workshops to support operational reporting and advanced analytics.

The role requires experience with SQL, Python, and cloud platforms, and involves collaboration with engineers, data scientists, and business stakeholders.