[Hiring] Principal, Data Engineer @L3HHCM20

Role Description

L3Harris Enterprise Data and AI team is seeking a Data Architect with experience in managing enterprise-level data life cycle processes. This individual will play a critical role in shaping our data architecture, ensuring the integrity, scalability, and efficiency of our systems. This includes overseeing data ETL/ELT pipelines, ensuring adherence to data and architectural standards, maintaining data frameworks, and ensuring data consolidation in our ontology or semantic layer. The selected individual will partner closely with development teams to design, review, and implement high quality data solutions within Palantir Foundry.

This position will support the company’s modern data platform, Unified Data Layer, focusing on data pipeline development and maintenance, data platform design, documentation, and user training. The goal is to ensure seamless access to data for all levels of the organization, empowering decision-makers with clean, reliable data.

• Provide architectural oversight for the company’s data platform and related initiatives, ensuring alignment with company standards and best practices
• Assist development initiatives with design reviews, offering guidance on architecture and data modeling
• Lead design reviews for proposed solutions, including data sourcing, data pipelines, data models, and ontology resources, providing actionable feedback to enhance design scalability
• Assist and develop architectural artifacts, perform requirements decomposition, and develop other documentation to support the software development lifecycle (SDLC)
• Support the SDLC process by participating in data architecture review sessions, reviewing proposed solutions for compliance with architectural standards
• Oversee and provide guidance for data pipelines, ensuring scalability, reusability, and performance
• Utilize Palantir Foundry to perform data integration and ontology management to support big data analytics at scale
• Collaborate with cross-functional teams to define data governance, metadata, and ontology standards, ensuring consistency and clarity across the data platform and enterprise
• Remain current with emerging data technologies and frameworks to recommend improvements to the data platform architecture

Qualifications

• Bachelor’s Degree and minimum 12 years prior Palantir experience or Graduate Degree and a minimum of 10 years of prior Palantir experience. In lieu of degree, minimum 16 years of prior Palantir experience
• 5+ years of experience as a data architect or in a senior data engineering role, ideally supporting enterprise-scale data and analytics platforms
• 4+ years of experience with Data Pipeline development or ETL tools such as Palantir Foundry, Azure Data Factory, SSIS or Python
• 5+ Years of overall Data Integration experience in Palantir Foundry or similar data integration tools

Requirements

• Hands on Experience with design, development of Data Pipelines in Palantir Foundry Pipeline Builder or Code Repository, or similar technologies leveraging PySpark and Spark SQL
• Experience architecting Palantir Foundry platforms to enable Generative AI capabilities, including Retrieval-Augmented Generation (RAG), semantic search, and LLM integration
• Experience with Palantir Foundry tools such as Ontology Manager, Compass, Code Repository, Solution Designer, OSDK, AI FDE, and AIP Analyst
• Demonstrated understanding of how Foundry's Ontology, operational workflows, and governed data assets enable AI-driven business and manufacturing solutions
• Familiarity with SDLC processes and architecture review or data governance board processes
• Understanding of BI (Business Intelligence) & DW (Data Warehouse) development methodologies
• Experience with Python, Pandas, Databricks, JavaScript, Typescript or other scripting languages
• Experience with AI tools such as OpenAI, Palantir AIP, Snowflake Cortex, or similar

Benefits

• Health and disability insurance
• 401(k) match
• Flexible spending accounts
• EAP (Employee Assistance Program)
• Education assistance
• Parental leave
• Paid time off
• Company-paid holidays