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Python Data Engineer with DEEP (Palantir experience)

Plano, TX, US • Posted 30+ days ago • Updated 3 days ago

Full Time

On-site

Fitment

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Job Details

Skills

Analytics
Data Integration
Python
Data Processing
Pandas
NumPy
PySpark
Development Management
Optimization
Ontologies
Data Engineering
Management
Extract
Transform
Load
ELT
Streaming
Scheduling
Workflow
Data Quality
Data Modeling
SQL
PostgreSQL
MySQL
NoSQL
MongoDB
Database
Data Warehouse
Big Data
Cloud Computing
Amazon Web Services
Microsoft Azure
Google Cloud
Google Cloud Platform
Apache Spark
Apache Hadoop
Amazon S3
Storage
HDFS

Summary

Job Description:

Python Data Engineer with DEEP (Palantir experience)

Data Engineer with strong proficiency in Python and hands-on experience working with Palantir platforms (Foundry, Gotham, or relevant Palantir tools).

The ideal candidate will design, build, and optimize data pipelines, support scalable analytics solutions, and ensure reliable data integration within complex environments.

Core Technical Skills:

Python Programming
Advanced knowledge of Python for data processing, ETL development, and automation.
Experience with popular libraries: pandas, numpy, pySpark.
Ability to write clean, efficient, and modular code following best practices.

Palantir Platforms

Practical experience on Palantir Foundry or Gotham (pipelines, data lineage, data modeling).
Development, management, and optimization of pipelines and data assets in Palantir environments.
Familiarity with Palantir's ontology, tools for data transformation, and logic building blocks.
Integration of external data sources with Palantir, leveraging APIs and connectors.

Data Engineering & ETL

Building, deploying, and managing scalable ETL/ELT pipelines (batch and streaming).
Experience with scheduling/orchestrating workflows via Airflow, Palantir Pipeline Builder, or similar.
Data quality, validation, profiling, and error handling.

Databases and Data Modeling

Proficient in SQL; able to work with relational (e.g. PostgreSQL, MySQL) and NoSQL (e.g. MongoDB) databases.
Experience designing efficient schemas, indexing strategies, and optimizing queries.
Understanding data warehousing concepts.

Cloud & Big Data

Experience with cloud platforms (AWS, Azure, Google Cloud Platform) and distributed data technologies (e.g. Spark, Hadoop).
Familiarity with scalable storage solutions (S3, Blob storage, HDFS).

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: RTL155990
Position Id: 6c1445e296bcf4cc8eb174349e92a3c9
Posted 30+ days ago

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