Job Description
Job Overview

Nextlink is seeking for a Data Engineer with strong expertise in Palantir Foundry, Python, and PySpark to design, develop, and maintain scalable data engineering solutions. The ideal candidate will have hands-on experience with Foundry Ontology, data pipelines, modular applications, and end-to-end data solution implementation, along with a solid understanding of data engineering principles and distributed computing.

Key Responsibilities
1. Palantir Foundry Platform Expertise

- Develop and maintain data pipelines, Foundry Ontology, and modular applications within the Palantir Foundry platform.

- Design and implement end-to-end data solutions, from data ingestion and transformation to data modeling and consumption.

- Integrate data from multiple source systems into Palantir Foundry.

- Build and maintain scalable, reusable data workflows aligned with business requirements.

- Leverage Foundry capabilities to support data-driven applications and analytics.

2. Programming and Scripting – Python & PySpark

- Develop Python and PySpark scripts for data processing, transformation, cleansing, and automation.

- Build reusable Python functions and libraries to extend Palantir Foundry capabilities.

- Develop modular and maintainable code for ETL workflows and data transformation processes.

- Process large datasets efficiently using Python libraries such as Pandas and Num Py, along with PySpark for distributed processing.

- Optimize code for performance, scalability, and reliability.

- Use SQL for data querying, validation, and data modeling, as required.

3. Data Engineering Fundamentals

- Design, develop, and maintain ETL/ELT pipelines for data ingestion and transformation.

- Build efficient data models and optimize data processing workflows.





- Work with structured and unstructured data from multiple sources.

- Implement data quality checks, validation, and error-handling mechanisms.

- Ensure data consistency, reliability, and availability across pipelines.

4. Big Data and Distributed Systems

- Develop scalable data processing solutions using Apache Spark and PySpark.

- Apply distributed computing concepts to handle large-scale data processing requirements.

- Troubleshoot pipeline failures and resolve data processing issues.

- Perform performance tuning and optimization of Spark jobs and data workflows.

- Follow best practices for scalable and efficient data engineering.

RequirementsEssential Skills

- Hands-on experience with Palantir Foundry and its core capabilities.

- Strong programming skills in Python and PySpark.

- Experience developing and maintaining ETL/ELT pipelines.

- Knowledge of Foundry Ontology, data pipelines, and modular applications.

- Strong understanding of data transformation, data modeling, and data integration.

- Experience with Apache Spark and distributed data processing.

- Understanding of performance optimization and scalable data processing techniques.

Desirable Skills

- Familiarity with SQL for querying and data modeling.

- Experience with Pandas and Num Py for data manipulation and analysis.

- Knowledge of data quality, validation, and pipeline monitoring practices.

- Experience integrating data from multiple source systems.





- Understanding of data governance and enterprise data engineering best practices.

Keywords

Palantir Foundry, Palantir Core, PySpark, Python, Apache Spark, Data Engineering, ETL/ELT, Foundry Ontology, Data Pipelines, Modular Applications, SQL, Data Transformation, Data Modeling, Distributed Computing, Performance Optimization.

Primary Skills: Digital – PySpark, Palantir Core

Role Focus: Palantir Foundry development, Python/PySpark-based data engineering, and end-to-end data pipeline implementation.

Requirements
Essential Skills and Qualifications 10+ years of experience in data modeling and data architecture. Strong hands-on experience in Data Vault 2.0 implementation. Extensive experience with Databricks, Lakehouse, Delta Lake, and Unity Catalog. Strong expertise in dimensional modeling, including Star and Snowflake schemas. Advanced SQL skills, including query optimization and performance tuning. Hands-on experience designing and implementing Bronze, Silver, and Gold data models. Strong understanding of metadata management, data lineage, data governance, and data quality. Experience in the Insurance or Financial Services domain. Hands-on experience with data modeling tools such as ERwin, SQLDBM, and ER/Studio. Working knowledge of Microsoft SQL Server 2019. Desirable Skills Experience in enterprise-scale data platform implementations. Knowledge of data architecture best practices and up-to-date data engineering principles. Experience implementing data governance and metadata management frameworks. Job Details Job Title: Senior Data Modeler – Data bricks Experience Required: 10+ years Primary Skills: Databricks, Data Vault 2.0, Data Architecture, Data Modeling, Microsoft SQL Server 2019 Work Locations: Trivandrum, Chennai, Bangalore, Kochi

📌 Data Engineer (India)
🏢 Next-Link
📍 India