Palantir Core Developer
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Role details
Tech stack
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Job description
We are seeking an experienced Palantir Data Engineer with over 10 years of IT experience and a strong background in data pipeline development, analytics, and Palantir Foundry. The ideal candidate should be skilled in Python, PySpark, AWS, and big data technologies such as Spark, Flink, Kafka, and Kubernetes., * Design, develop, and support Palantir Foundry data pipelines and applications.
- Work with Palantir components: Core, Quiver, Slate, Map, Contour, Hubble, Workshop, Notepad, and Pipeline Builder.
- Perform large-scale data analysis and implement data ingestion/storage solutions in AWS.
- Write efficient code using Python/PySpark; optimize SQL/PySQL queries.
- Manage ontology, data lineage, and data structures within Palantir.
- Collaborate with cross-functional teams in an Agile environment.
- Maintain and enhance existing reporting applications; develop new ones as needed.
Requirements
Data Sets, Data Management, Data Analysis, GitHub, Python Programming/Scripting Language, Scalable System Development, SQL (Structured Query Language), Gradle, Agile Programming Methodologies, Amazon Web Services (AWS), We are seeking a Palantir Foundry Developer with 8+ years of hands-on expertise in Palantir Foundry. The role involves designing, developing, and maintaining data pipelines, analyzing large-scale datasets, and integrating data from multiple sources using Palantir components such as Core, Quiver, Slate, Map, and Pipeline Builder.
The candidate should have strong proficiency in Python, PySpark, SQL/PySQL, and experience working with AWS, Spark, Flink, Kafka, Kubernetes, Gradle, Webpack, and GitHub. Responsibilities include building scalable data workflows, supporting Foundry work packets, managing data lineage, and collaborating across teams in an Agile environment.
Excellent communication, analytical, and problem-solving skills are essential, along with the ability to work independently in a fast-paced setting., * Strong proficiency in Python, PySpark, SQL/PySQL.
- Hands-on with AWS, Spark, Kafka, Flink, Kubernetes, Gradle, Webpack, GitHub.
- Strong problem-solving, communication, and collaboration skills.
- Experience handling large-scale data systems and process optimization.
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