Description

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.

Azure Knowledge Expected 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

Enable Skills-Based Hiring No ECMS REQ IDAdditional Details

- ECMS REQ ID : 584712
- Project Location 1 : KRNK | Bengaluru
- Project Location 2 : (No Value)
- Project Location 3 : (No Value)
- Project Location 4 : (No Value)
- Delivery SPOC : V Chaitanya / Pavan Chalasani
- Relevant Experience : 4 to 7 Years
- Mandatory skills :



Mandatory Skills and Experience • 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. • Positive hands-on proficiency in PySpark and a sound understanding of Apache Spark and distributed dataprocessing concepts. • Basic knowledge or working experience in Azure Data Engineering. • Strong analytical, debugging, and problem-solving skills. • Effective communication and stakeholder-management skills. • Ability to work proactively in a support-oriented environment and take ownership of operational issues.
- Desired skills : Preferred Skills • 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.
- Domain (Industry) : Oil and Gas
- BGC (Before onboarding / After onboarding) : PostOB
- Total Experience (Ex. 5-7 Years) : 7 Years
- BGC Details : Infosys Standard Checklist
- BGC Vendor : Any NASSCOM Vendor
- Mode of Interview : Face to Face
- WFO / WFH / Hybrid : Hybrid
- Please enter shift timings : 9 AM to 6 PM
- Shift Timings : General

📌 584712 | Palantir Foundry Data Engineer | IC | Bengaluru
🏢 Trigent Software
📍 Bengaluru