Role: Palantir Data Engineer
Mandatory Skills
Palantir Foundry / Palantir Core
Python
PySpark
ETL Pipeline Development
Data Engineering
Spark (PySpark)

Key Responsibilities
Design and implement end-to-end data solutions using Palantir Foundry.
Develop and maintain Foundry Ontology, pipelines, and modular applications.
Build scalable ETL pipelines for data ingestion, transformation, and processing.
Develop reusable Python and PySpark code for data engineering workflows.
Integrate data from multiple source systems into the Palantir platform.
Optimize data processing performance using Python libraries and PySpark.
Design effective data models and workflows for structured and unstructured data.
Work with distributed data processing frameworks and optimize Spark jobs.

Required Technical Skills
Hands-on experience with Palantir Foundry (Ontology, Pipelines,



Modular Applications)
Solid programming skills in Python and PySpark
Experience in building scalable ETL pipelines
Strong understanding of Data Engineering concepts
Experience with Apache Spark and distributed computing
Performance tuning and optimization of Spark/PySpark jobs

Good-to-Have Skills
SQL
Data Modeling
Pandas and NumPy
Experience handling large-scale structured and unstructured datasets

Candidate Profile
8+ years of overall IT experience.
Minimum 6+ years of relevant experience in Palantir Foundry.
Solid problem-solving and analytical skills.
Experience in enterprise-scale data engineering projects.
Good communication and collaboration skills.

📌 Palantir Data Engineer Bengaluru
🏢 Tekskills India Private
📍 Bengaluru