[Hiring] FBS Associate Data Engineer @Capgemini

Role Description

The Life Data Platform (LDP) & Data Enablement team is responsible for acquiring, integrating, governing, modeling, and publishing enterprise data across on-premises and cloud platforms. The team enables trusted, scalable, and business-ready data products, analytics, reporting, and operational insights for Life Insurance functions through AWS, Dremio, Data Catalog, and modern data engineering practices.

The Associate Data Engineer will support the design, development, and maintenance of data pipelines, data models, and enterprise data products that enable reporting, analytics, and operational use cases. This role combines hands-on data engineering with stakeholder collaboration, working closely with data engineers, business partners, analysts, and technology teams to deliver reliable and scalable data solutions while growing technical expertise in cloud-based data platforms.

Key Responsibilities

• Develop, maintain, and support scalable data pipelines and data integration solutions.
• Assist in building and supporting enterprise data products for reporting, analytics, and operational use cases.
• Develop and maintain data models, data warehouses, and dimensional modeling solutions with guidance from senior team members.
• Integrate data from internal systems, cloud platforms, APIs, and third-party vendors.
• Partner with stakeholders to understand business requirements and translate them into technical solutions.
• Support data quality, governance, reliability, and consistency initiatives.
• Optimize SQL queries and troubleshoot data processing issues.
• Work within AWS-based data platforms and modern data engineering frameworks.
• Participate in Agile ceremonies, project planning, and sprint activities.
• Follow engineering best practices, coding standards, and governance processes.
• Contribute to continuous improvement efforts across data architecture and platform capabilities.

Qualifications

• 4-6 years of total professional experience.
• 2-4 years of experience in Data Engineering, Data Integration, Analytics Engineering, or related disciplines.
• Fluent English (written and verbal).
• Bachelor's degree in a technical, engineering, quantitative, or related discipline preferred.
• Experience working with cloud-based data environments.
• Strong communication and collaboration skills.

Requirements

• Python
• AWS Glue
• PySpark
• SQL Development & Query Performance Tuning
• Data Warehousing
• Dimensional Modeling
• REST API Integration
• Data Modeling & Data Analysis
• Enterprise Data Integration
• Data Pipeline Development
• Cloud Data Platforms

Preferred

• AWS ecosystem experience
• Dremio
• Data Catalog technologies
• Experience supporting analytical and operational data products
• Experience in Life Insurance, Financial Services, or regulated industries
• Experience working with external vendors and cross-functional teams
• Cloud or Data Engineering certifications (AWS, Azure, Databricks, Snowflake, Dremio, GCP, etc.)

Business Knowledge

• Ability to collaborate with technical and non-technical stakeholders.
• Strong communication and stakeholder management capabilities.
• Experience translating business requirements into technical solutions.
• Understanding of data governance, data quality, and reporting concepts.
• Experience working within regulated industries preferred.
• Life Insurance industry experience is a plus.
• Ability to balance hands-on development with stakeholder collaboration.

Benefits

• Competitive salary and performance-based bonuses
• Comprehensive benefits package: Grocery vouchers, saving funds, SGMM, etc.
• Career development and training opportunities
• Dynamic and inclusive work culture within a globally renowned group
• Private Health Insurance
• Pension Plan
• Paid Time Off
• Training & Development