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
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).
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