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# Data Engineer

- **Company:** Promantus Inc
- **Location:** Plano, TX, United States
- **Contract:** Contract
- **Skills:** Application Programming Interfaces (APIs), Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Big Data, Cloud Computing, Profiling, Databases, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Digital Assets, Distributed Data Store, Apache Hadoop, Hadoop Distributed File System, Python (Programming Language), PostgreSQL, MongoDB, MySQL, NoSQL, NumPy, Standard Sql, Data Streaming, Data Processing, Google Cloud, Palantir Foundry, Database Optimization, Apache Spark, Pandas, Pyspark, Data Lineage, Data Pipelines
- **Published:** October 30, 2026
- **Apply:** https://www.dice.com/job-detail/25f114f1-c4fb-4b2b-9342-ad19e6c14b4f

## About the Role

* 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 using Palantir
 * 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).

## Description

* Python Data engineer with DEEP (Palantir experience)