Data Engineer - Build Scalable Solutions with Python AWS Spark Palantir Foundry
Overview
We seek a skilled Data Engineer to lead data pipeline development and platform scaling for mission-critical projects. You will architect robust ETL workflows and drive data transformation initiatives across diverse datasets. This role offers unique exposure to intelligence and technology domains while supporting impactful missions.
What You'll Do11
- 1Design and implement scalable ETL/ELT pipelines using Python and Spark SQL
- 2Develop and maintain data transformations in Palantir Foundry Data Pipeline Builder
- 3Debug and resolve issues within Palantir Foundry environments
- 4Create scripts for data format conversion and platform scalability support
- 5Collaborate with cross-functional teams to operationalize data solutions
- 6Optimize data ingestion processes using distributed computing frameworks
- 7Establish monitoring protocols for data platform performance
- 8Implement object-oriented data models in Foundry Ontology
- 9Support real-time data streaming architectures with Kafka integration
- 10Ensure compliance with security standards for classified information systems
- 11Drive continuous improvement of data infrastructure through automation
Requirements10
- 15+ years building ETL pipelines with Spark and Airflow
- 23+ years experience with Palantir Foundry and Object Types
- 3Bachelor's degree with secret clearance authorization
- 4Proficiency in Python SQL Scala Java
- 5Experience with AWS Redshift Snowflake and cloud platforms
- 6Background in NoSQL databases MongoDB Cassandra
- 7Familiarity with containerization technologies Docker Kubernetes
- 8Agile methodology expertise in software development
- 9Ability to work in high-pressure environments with clear deadlines
- 10Strong problem-solving skills for complex data challenges
Salary Insight
$78 - $176k per year
Location
Required Skills
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