Data Engineer

Company:Global Banking Organization

Key Skills: Python, PySpark, Spark SQL, Data Pipelines, Big Data, Palantir Foundry, Hive, Hadoop, SQL, AWS, Azure, JavaScript, HTML, CSS, Analytics, Data Visualization, Reinsurance Domain

Roles and Responsibilities:

• Implement data pipelines and analytics solutions to support key decision-making in Life & Health Reinsurance.
• Work closely with Product Owners and Engineering Leads to understand requirements and evaluate implementation efforts.
• Develop and maintain scalable data transformation pipelines to handle large data volumes.
• Implement analytics models and build data visualizations to provide actionable insights.
• Collaborate within a global development team to design and deliver cutting-edge solutions using Big Data and Machine Learning technologies.

Experience Requirement:

• 0-3 years of experience working with large-scale software systems in data engineering or analytics.
• Hands-on experience building scalable data transformation pipelines using Python/PySpark.
• Proficiency in SQL, preferably Spark SQL, for managing and transforming large datasets.
• Exposure to working with enterprise data platforms and distributed computing environments like Spark, Hive, or Hadoop.
• Practical knowledge of developing solutions in cloud environments such as AWS or Azure.
• Familiarity with Palantir Foundry is a strong advantage.
• Experience with JavaScript/HTML/CSS is a plus.
• Demonstrated analytical and problem-solving skills in data-centric projects.
• Ability to work in a global, cross-functional team and effectively communicate complex data insights.

Education: Any Post Graduation, Any Graduation.