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# Lead, Data Engineer

- **Company:** L3Harris Technologies, Inc.
- **Location:** Melbourne, FL, United States (Remote available)
- **Experience:** Expert
- **Salary:** $127,000.0 - $236,500.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), Artificial Intelligence, ARM Architecture, Big Data, Data Architecture, Data Cleansing, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Apache Hive, Python (Programming Language), Metadata, Systems Development Life Cycle, Search Technologies, Software Engineering, SQL Server Integration Services, TypeScript, Enterprise Data Management, Scripting, Azure Data Factory, Large Language Models, Snowflake, Generative AI, Data Layers, Pandas, Pyspark, Integration Frameworks, Data Pipelines, Databricks
- **Published:** July 17, 2026
- **Apply:** https://www.clearancejobs.com/jobs/9038829/lead-data-engineer

## About the Role

* Bachelor's Degree and minimum 9 years prior Palantir experience or Graduate Degree and a minimum of 7 years of prior Palantir experience In lieu of degree, minimum 13 years of prior Palantir experience.
 * Minimum of 4 years of experience with Data Pipeline development or ETL tools such as Palantir Foundry, Azure Data Factory, SSIS, or Python.
 * Minimum of 4 years of experience in Data Integration.

Preferred Additional Skills:

 * Experience supporting or implementing solutions that leverage 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
 * 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
 * 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
 * Familiarity with SDLC processes and architecture review or data governance board processes

## Description

L3Harris Enterprise Data and AI team is seeking a Data Engineer with experience in managing enterprise-level data life cycle processes. This role includes overseeing data ETL/ELT pipelines, ensuring adherence to data standards, maintaining data frameworks, conducting data cleansing, orchestrating data pipelines, and ensuring data consolidation. The selected individual will play a pivotal role in maintaining ontologies, building scalable data solutions, and developing dashboards to provide actionable insights for the enterprise 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


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