Palantir Foundry Data Engineer
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Job Location:
Detroit, MI - USA
Monthly Salary:
Not Disclosed
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
Required qualifications to be successful in this role
Strong proficiency with Palantir Foundry including experience with tools like Pipeline Builder Code Workbooks Ontology Manager and Quiver.
Advanced skills in data engineering particularly with PySpark Python and SQL.
Experience designing and implementing complex ontologies within Palantir Foundry including creating Object Types Link Types and Property Types.
Expertise in developing and managing data pipelines including batch incremental and streaming pipelines.
Proficiency in semantic object linking and leveraging Foundrys semantic model for data transformation and enrichment.
Knowledge of data quality processes and the ability to implement testing and codification methods.
Understanding of program management principles and the ability to work in Agile/Scrum development teams.
Strong communication skills and the ability to collaborate with various stakeholders including product owners and end-users.
Strong proficiency with Palantir Foundry including experience with tools like Pipeline Builder Code Workbooks Ontology Manager and Quiver.
Advanced skills in data engineering particularly with PySpark Python and SQL.
Experience designing and implementing complex ontologies within Palantir Foundry including creating Object Types Link Types and Property Types.
Expertise in developing and managing data pipelines including batch incremental and streaming pipelines.
Proficiency in semantic object linking and leveraging Foundrys semantic model for data transformation and enrichment.
Knowledge of data quality processes and the ability to implement testing and codification methods.
Understanding of program management principles and the ability to work in Agile/Scrum development teams.
Strong communication skills and the ability to collaborate with various stakeholders including product owners and end-users.
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
