Data Engineer

About Company :

Our client is a global technology consulting and digital solutions company, resulting from the merger . It focuses on helping businesses leverage digital technologies to reimagine business models, accelerate innovation, and drive growth. The company provides services across various industries, including digital transformation, consulting, and application development.

Role : Data Engineer

Location : Bengaluru

Experience : 2-4Yrs

Interview Mode : virtual

Work mode : Hybrid

Job type : C2H

Immediate Joiner's +15 Day's

JOB DESCRIPTION :

We are seeking a highly skilled and detail-oriented Data Engineer with expertise in data architecture, pipeline development, cloud platforms, and big data technologies. The ideal candidate will be responsible for designing, building, and maintaining scalable data infrastructure, ensuring efficient data flow across systems, and enabling advanced analytics and machine learning capabilities.

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Key Responsibilities :

Good to Have – Palantir Foundry Experience :

Experience working with Foundry Ontology to model enterprise data and define semantic relationships.

Building and maintaining Code Workbooks and Data Pipelines within Foundry for scalable ETL / ELT workflows.

Familiarity with Foundry's Object Explorer and Data Lineage tools for tracking data transformations and dependencies.

Integration of Foundry with external systems using Foundry APIs and Data Connections.

Experience with Foundry's Operational Workflows for automating data-driven decision-making.

Understanding of Foundry's security model and access control for enterprise-grade data governance.

• Design, develop, and maintain ETL / ELT pipelines for structured and unstructured data.
• Build and optimize data lakes, data warehouses, and real-time streaming systems.
• Collaborate with Data Scientists and Analysts to ensure data availability and quality for modeling and reporting.
• Implement data governance, security, and compliance protocols.
• Develop and maintain data APIs and services for internal and external consumption.
• Work with cloud platforms (AWS, Azure, GCP) to deploy scalable data solutions.
• Monitor and troubleshoot data workflows, ensuring high availability and performance.
• Automate data validation, transformation, and integration processes.
• Manage large-scale datasets using distributed computing frameworks like Spark and Hadoop.
• Stay updated with emerging data engineering tools and best practices.

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Technical Skills :

Programming & Frameworks :

Cloud & DevOps :

Databases :

Data Architecture & Processing :

Monitoring & Visualization :

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Qualifications :