Palantir Foundry Developer

Position:
Palantir Foundry Developer

Company:
Weekday's Client

Location:
India, Pune

Employment type:
Full-time

Short Summary:
We are looking for a skilled Palantir Foundry Developer with 3–7 years of experience in designing, developing, and optimizing enterprise-scale data platforms and analytics solutions. The ideal candidate should have hands-on expertise in Palantir Foundry, Azure Databricks, and Azure Data Lake.

Responsibilities:
- Design, develop, and maintain scalable data pipelines using Palantir Foundry.
- Build and optimize data workflows, transformations, and ontology models within the Foundry platform.
- Integrate data from multiple structured and unstructured sources into enterprise data ecosystems.
- Develop and maintain ETL/ELT processes using Azure Databricks and Spark.
- Design, implement, and manage data storage solutions using Azure Data Lake.
- Collaborate with business users to gather requirements and translate them into technical data solutions.
- Build reusable data assets, pipelines, and workflows that improve data accessibility and reliability.
- Optimize data processing performance and ensure high availability of data pipelines.
- Monitor data quality, troubleshoot pipeline failures, and implement robust validation mechanisms.
- Work closely with cloud engineers and architects to deploy secure and scalable data solutions.
- Participate in code reviews, testing, documentation, and release management activities.
- Ensure compliance with security, governance, and data management best practices.
- Stay updated with the latest advancements in Palantir Foundry, Azure cloud services, and modern data engineering technologies.

Requirement:
- Strong hands-on experience with Palantir Foundry development and implementation.
- Experience building data pipelines, Code Repositories, Pipeline Builder, Workshop, and Ontology in Foundry.
- Proficiency in Azure Databricks and Apache Spark for large-scale data processing.
- Experience working with Azure Data Lake (ADLS Gen2) for enterprise data storage.
- Strong understanding of ETL/ELT concepts and modern data engineering methodologies.
- Experience working with SQL and data transformation techniques.
- Familiarity with Python or PySpark for data engineering tasks.
- Knowledge of distributed data processing frameworks.
- Understanding of data modeling, metadata management, and data governance principles.
- Experience integrating APIs and external data sources.

Benefits:
- Opportunity to work on impactful, enterprise-grade solutions.
- Collaborative environment that drives innovation through data.