This role pays more than
67%
of similar roles. Most pay
$169,550–$235,750
— the shaded band above.
At the midpoint, this role pays about
$218k
versus about
$203k
for comparable roles.
Based on 239 similar postings.
Employer
About L3Harris
L3Harris Technologies is a US aerospace and defense technology company providing space and airborne systems, communications, electronic warfare, and missile propulsion solutions for government and commercial customers.
L3Harris currently has
470 open roles
on FindRole.
Listed pay typically runs
$106,500–$197,500
across 185 roles with salary data.
The Principal, Data Engineer joins the Enterprise Data and AI team to manage enterprise-level data lifecycle processes and shape the organization's data architecture. This individual will oversee ETL/ELT pipelines, maintain data frameworks, ensure consolidation in the ontology or semantic layer, and provide architectural oversight for the Unified Data Layer. The role involves performing requirements decomposition, conducting design reviews for data models, and ensuring scalability across the platform. Key technical requirements include extensive experience with Palantir Foundry, including Pipeline Builder, Code Repository, and Ontology Manager, alongside proficiency in Python, PySpark, Spark SQL, and Pandas. Candidates may also utilize tools like Azure Data Factory, Databricks, or Snowflake Cortex. The position focuses on solving complex data integration challenges to provide clean, reliable data for big data analytics and generative AI capabilities like Retrieval-Augmented Generation.
What does a Data Engineer earn in Remote?
Median $179125 from 30 postings across 20 companies.
Provide architectural oversight for the company's data platform to ensure alignment with corporate standards and best practices.
Conduct design reviews for data sourcing, pipelines, models, and ontology resources to improve scalability.
Develop architectural artifacts and documentation to support the software development lifecycle (SDLC).
Oversee the development of scalable, reusable, and high-performing data pipelines.
Utilize Palantir Foundry to perform large-scale data integration and ontology management.
Define data governance, metadata, and ontology standards in collaboration with cross-functional teams.
Monitor emerging technologies to recommend continuous improvements to the data platform architecture.
What we're looking for
Bachelor's degree and 12 years of Palantir experience, a Graduate degree and 10 years of Palantir experience, or 16 years of Palantir experience without a degree.
At least 5 years of experience as a data architect or in a senior data engineering role for enterprise-scale platforms.
At least 4 years of experience with Data Pipeline development or ETL tools such as Palantir Foundry, Azure Data Factory, SSIS, or Python.
At least 5 years of overall Data Integration experience in Palantir Foundry or similar tools.
Must be a U.S. citizen to obtain a security clearance.
Experience with PySpark and Spark SQL for data pipeline development (preferred).
Experience architecting Palantir Foundry platforms for Generative AI capabilities like RAG, semantic search, and LLM integration (preferred).
Proficiency in Python, Pandas, Databricks, JavaScript, or other scripting languages (preferred).
Palantir Foundry
Ontology
Python
PySpark
SQL
Microsoft Fabric
Databricks
Snowflake
Azure Synapse
Power BI
ETL
ELT
Data Modeling
Data Governance
Semantic Modeling
Lakehouse Architecture
Data Lineage
C
Assembly
Android
iOS
Objective-C
Swift
Java
Kotlin
IDA Pro
Ghidra
Hopper
Frida
ADB
Git
GitLab CI
CMake
Reverse Engineering
Offensive Cyber Security
System Engineering