Palantir Data Engineer

Tekskills Inc.; Dadri; On-site; INR 1,400,000 - 2,400,000; Full time

Job summary

Tekskills Inc. is looking for a Palantir Data Engineer with 6+ years of experience to join our Hyderabad team. The role focuses on Palantir Foundry platform expertise, building end-to-end data solutions, and data pipeline development.

The candidate will leverage Python and PySpark for data processing, automation, and scalable ETL workflows, with emphasis on data modeling, performance tuning, and working with large datasets.

Qualifications

• Experience with Palantir Foundry platform and End-to-End data solutions.
• Proficient in Python and PySpark for data processing and automation.
• Experience building ETL pipelines and data modeling.
• Familiarity with SQL for querying and data modeling is a plus.

Responsibilities

• Develop Palantir Foundry data pipelines and modular applications.
• Implement end-to-end data solutions sourcing data from various systems.
• Design and optimize ETL workflows for performance and reliability.
• Collaborate with data teams to model, transform, and enrich datasets.

Skills

Palantir Platform Expertise

Python & PySpark

Data Engineering Fundamentals

Big Data & Distributed Systems

Tools

PySpark

Spark

Pandas

NumPy

SQL

Job description

Role : Palantir Data Engineer

Experience 6+ yrs

Location - hyderabad

Technical Skills

1. Palantir Platform Expertise

• Working with Foundry Ontology, pipelines, and modular applications.
• Implementing End to End data Solutions in Palantir sourcing data from

2. Programming & Scripting (Python and PySpark)

• Data Processing & Automation: Ability to clean, transform, and process large datasets efficiently.
• Integration with Palantir Foundry: Build custom Python functions and libraries to extend Foundrys capabilities.
• Pipeline Development: Write modular, reusable code for ETL workflows and data transformations.
• Performance Optimization: Use Python libraries like Pandas, NumPy, and PySpark for scalable data operations.
• Familiarity with SQL for querying and data modeling. Good to have

3. Data Engineering Fundamentals

• Building ETL pipelines for ingestion and transformation.
• Designing data models and optimizing workflows.
• Handling structured and unstructured data.

4. Big Data & Distributed Systems

• Experience with Spark (PySpark) for scalable data processing.
• Understanding of parallel computing and performance tuning.