Job Summary We are seeking a skilled Data Engineer with strong hands-on experience in Palantir Foundry and good proficiency in SQL, Python and PySpark. The candidate should also have basic knowledge or practical exposure to Azure Data Engineering technologies. Palantir Foundry is the primary skill for this role, while Azure Data Engineering is secondary. The role involves supporting data pipelines, workflows and applications while ensuring operational stability, data quality and effective stakeholder collaboration. The ideal candidate is Palantir-first: someone who can contribute immediately within Palantir Foundry, is comfortable working hands-on with SQL, Python and PySpark, and has enough Azure Data Engineering knowledge to collaborate across the wider data platform. Strong Azure expertise is beneficial but should not substitute for meaningful Palantir Foundry experience.

Key Responsibilities
• Support, maintain and enhance Palantir Foundry applications, data pipelines, datasets and operational workflows.
• Develop data transformation and processing logic using SQL, Python and PySpark.
• Troubleshoot data pipeline, workflow and application issues and drive them through to resolution.
• Monitor data workflows and proactively identify failures, performance bottlenecks and data-quality issues.
• Implement data validation, cleansing, reconciliation and monitoring controls to improve reliability.
• Work with large and complex datasets to support analytics, reporting and operational use cases.
• Collaborate with business stakeholders, application teams and engineering teams to understand requirements and deliver practical solutions.
• Apply basic Azure Data Engineering knowledge when working with cloud-based data ingestion, storage and processing components.
• Contribute to process improvement, automation, technical documentation and support handover activities.
• Follow applicable data security, governance, access-control and compliance standards.



Role Requirements and

Qualifications:
• Strong hands-on experience with Palantir Foundry, including practical exposure to data pipelines, workflows, datasets, applications or platform support.
• Good hands-on proficiency in SQL for data extraction, transformation, validation and troubleshooting.
• Good hands-on proficiency in Python for data processing, automation and support utilities.
• Good hands-on proficiency in PySpark, with a sound understanding of Apache Spark and distributed data processing concepts.
• Basic knowledge or working experience in Azure Data Engineering. Working knowledge or basic exposure to one or more of the following is desirable:
• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS)
• Azure SQL Database
• Azure Blob Storage
• Azure Databricks
• Azure DevOps and basic CI/CD practices
• Strong analytical, debugging and problem-solving skills.
• Effective communication and stakeholder-management skills.
• Ability to work proactively in a support-oriented workplace and take ownership of operational issues. Preferred

Qualifications:
• Experience supporting production data platforms or business-critical data applications.
• Familiarity with data-quality monitoring, incident management, root-cause analysis and service-support processes.
• Exposure to modern data-platform architecture, ETL/ELT patterns and cloud data services.
• Understanding of data governance, security, lineage and access-control principles.
• A proactive learning mindset and willingness to strengthen Azure Data Engineering capabilities. Why Join Us:
• Opportunities to work on transformative data and AI projects with leading global organizations.
• Continuous investment in learning, upskilling and professional development.
• Collaborative work environment with experienced technology professionals.
• Competitive compensation and comprehensive employee benefits.
• A culture that encourages innovation, ownership and career growth.

📌 Azure Data Engineer Palantir (Pune)
🏢 AceNet
📍 Pune