Our Client is one of the United States’ largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, our Client is part of one the largest Insurance Groups in the world.
Job Summary
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 modern cloud-based data technologies and data engineering practices.
The Data Engineer will be responsible for designing, developing, and supporting scalable data pipelines, data models, and enterprise data products that drive reporting, analytics, and operational business capabilities. This role combines hands-on data engineering with stakeholder engagement, working closely with business partners, analytics teams, technology teams, and external vendors to deliver high-quality data solutions and establish a trusted source of enterprise data.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and data integration solutions.
- Build and support enterprise data products for analytics, reporting, and operational use cases.
- Develop and maintain data models, data warehouses, and dimensional modeling solutions.
- Integrate data from internal systems, cloud platforms, APIs, and third-party vendors.
- Collaborate with business stakeholders to gather requirements and translate business needs into technical solutions.
- Ensure data quality, governance, reliability, and consistency across platforms.
- Optimize SQL queries and data processing performance.
- Support cloud-based data platforms and modern data engineering frameworks.
- Partner with external vendors and cross-functional teams to deliver successful data initiatives.
- Provide technical leadership, mentoring, and guidance on data engineering best practices.
- Support project planning, estimation, and execution in Agile environments.
- Drive continuous improvements in data architecture, automation, and data platform capabilities.
Requirements
Required Qualifications
- 7–9 years of total professional experience.
- 4–6+ years of experience in Data Engineering, Analytics Engineering, Data Integration, or related disciplines.
- Fluent English (written and verbal).
- Bachelor's degree in a technical, engineering, quantitative, or related discipline preferred.
- Experience working in cloud-based data environments.
- Strong stakeholder management and communication skills.
Technical Skills
Required:
- Python (4-6 years)
- AWS Glue
- PySpark
- SQL Development
- Data Warehousing
- REST API Integration
- Data Modeling & Data Analysis
- Data Pipeline Development
- Cloud Data Platforms
Preferred/Nice-to-have:
- AWS ecosystem experience
- Data Catalog technologies
- Experience with Life Insurance data environments
- Experience supporting analytical and operational data products
- Experience working with external vendors and TPAs
- Cloud or Data Engineering certifications (AWS, Azure, Snowflake, Databricks, Dremio, GCP, etc.)
- Enterprise Data Integration
- Solution Design & Data Architecture
- Dimensional Modeling
- Query Performance Tuning
Business Knowledge
- Ability to partner effectively with technical and non-technical stakeholders.
- Strong communication and stakeholder management capabilities.
- Experience translating business requirements into scalable technical solutions.
- Ability to lead technical discussions and provide subject matter expertise.
- Experience working within regulated industries preferred.
- Life Insurance industry experience is a strong plus.
- Ability to balance hands-on engineering work with stakeholder engagement and project leadership.
Benefits
Competitive compensation and benefits package:
- 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
Note: Benefits differ based on employee level.
By applying for this position, candidates acknowledge and agree that:
• Personal Data Processing: The personal data provided during the recruitment and selection process will be collected, processed, and retained for legitimate recruitment and compliance purposes, in accordance with applicable data protection and privacy laws and FBS internal policies.
• Legal Authorization to Work: Employment with FBS is conditional upon the candidate having valid, local legal authorization to work in the country where the role is based at the time of hire. FBS does not sponsor or obtain work authorization unless explicitly stated.
• Exclusivity of Employment and Conflict of Interest: Upon acceptance of an offer and during employment with FBS, employees will not be permitted to engage in parallel employment, professional activities, or paid work for other entities. Any ownership, partnership, directorship, or participation in other businesses or companies must be fully disclosed and formally reviewed in accordance with FBS internal conflict‑of‑interest and external engagement policies prior to the start date or as soon as such circumstances arise.
Failure to comply with these conditions may impact the hiring decision or employment continuation.
Skills Required
- 7-9 years of total professional experience
- 4-6+ years of experience in Data Engineering, Analytics Engineering, Data Integration, or related disciplines
- Fluent English, written and verbal
- Bachelor's degree in a technical, engineering, quantitative, or related discipline
- Experience working in cloud-based data environments
- Strong stakeholder management and communication skills
- Python experience of 4-6 years
- AWS Glue experience
- PySpark experience
- SQL development experience
- Data warehousing experience
- REST API integration experience
- Data modeling and data analysis experience
- Data pipeline development experience
- Cloud data platform experience
- AWS ecosystem experience
- Data Catalog technology experience
- Experience with Life Insurance data environments
- Experience supporting analytical and operational data products
- Experience working with external vendors and TPAs
- Cloud or Data Engineering certifications
- Enterprise data integration experience
- Solution design and data architecture experience
- Dimensional modeling experience
- Query performance tuning experience
- Ability to partner with technical and non-technical stakeholders
- Experience translating business requirements into scalable technical solutions
- Ability to lead technical discussions and provide subject matter expertise
- Experience working within regulated industries
- Life Insurance industry experience
- Ability to balance hands-on engineering with stakeholder engagement and project leadership
Capgemini Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Capgemini and has not been reviewed or approved by Capgemini.
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Healthcare Strength — Health coverage is positioned as comprehensive, spanning medical, dental, and vision alongside life and AD&D options. Additional wellbeing supports like employee assistance programs, gym discounts, and pet insurance broaden the value beyond core insurance.
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Parental & Family Support — Family-related benefits include maternity/paternity leave and broader family-forming support such as fertility and surrogacy assistance in some locations. Inclusive caregiving supports like back-up child and elder care and out-of-state medical travel are also highlighted.
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Equity Value & Accessibility — Equity participation is available through recurring employee share ownership or purchase programs, creating a longer-term wealth-building option in addition to salary. Eligibility and local access can vary, so confirming participation windows and requirements is important.
Capgemini Insights
What We Do
Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of 270,000 team members in nearly 50 countries. With its strong 50 year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group reported in 2020 global revenues of €16 billion.
