Data Engineer - Palantir Foundry

Data Engineer - Palantir Foundry

We are looking for a skilled Data Engineer with hands-on experience in PySpark, Python, SQL, and the Palantir Foundry platform. The candidate will be responsible for designing, developing, and maintaining scalable data pipelines and analytics solutions to support enterprise data processing, reporting, and business intelligence requirements.

Key Responsibilities :

• Design, develop, and maintain scalable and reliable data pipelines using PySpark, Python, SQL, and Palantir Foundry.

• Build and implement data engineering solutions for enterprise analytics, reporting, and data processing requirements.

• Perform data ingestion, transformation, cleansing, validation, and integration across multiple data sources.

• Develop and optimize data processing workflows using distributed computing technologies such as Spark, Hive, or Hadoop.

• Apply data modelling and data transformation techniques to support analytical use cases.

• Write and optimize complex SQL queries, preferably using Spark SQL, to ensure efficient data processing and retrieval.

• Work on the Palantir Foundry platform to develop and manage data pipelines and analytics solutions.

• Understand business and customer requirements and translate them into appropriate technical designs and data architectures.

• Ensure data quality, consistency, reliability, and accuracy across data pipelines and datasets.

• Troubleshoot data pipeline issues, optimize performance, and implement best practices for scalable data processing.

• Collaborate with business stakeholders, data analysts, and technical teams to deliver data-driven solutions.

• Maintain technical documentation for data pipelines, data models, transformation logic, and data workflows.

Required Skills & Qualifications :

• Minimum 2+ years of experience in data engineering or data development.

• Mandatory hands-on experience with the Palantir Foundry platform.

• Strong programming skills in Python and PySpark.

• Proficiency in SQL, preferably Spark SQL, including query development and optimization.

• Experience building and maintaining scalable data pipelines and data transformation workflows.

• Strong understanding of data modelling, data integration, data quality, and end-to-end data management.

• Experience working with distributed data processing technologies such as Apache Spark, Hive, or Hadoop.

• Ability to understand business requirements and translate them into technical designs and data solutions.

• Strong analytical, problem-solving, and troubleshooting skills.

• Good communication and collaboration skills to work effectively with cross-functional teams