Associate Data Engineer - AWS & PySpark Insurance Career

Capgemini; United States; Remote; USD 90,000 - 150,000; Full time

Benefits offered by this job

Private Health Insurance

Pension Plan

Paid Time Off

Training & Development

Job summary

Capgemini is seeking an Associate Data Engineer to contribute to a Life Insurance data platform, leveraging AWS Glue, PySpark, Dremio, and Data Catalog. The role emphasizes mentorship from senior engineers, involvement in architecture decisions, and governance frameworks to support learning and growth within a large enterprise data team.

You will design, develop, and maintain pipelines and data models, collaborating with analysts, business partners, and technology teams to deliver reliable data

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.

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.

Skills

Python

AWS Glue

PySpark

SQL

Data Warehousing

Dimensional Modeling

REST API Integration

Data Modeling

Stakeholder Communication

Education

Bachelor's degree

Tools

Dremio

Data Catalog

AWS Ecosystem

Job description

This Associate Data Engineer role sits within a large, enterprise-scale Life Insurance data platform team, offering exposure to a modern AWS-based stack including Glue, PySpark, Dremio, and Data Catalog — all high-demand, market-relevant tools in 2024-2025 data engineering.

Career development signals are strong: the role explicitly includes mentorship from senior engineers, involvement in architecture decisions, and contribution to governance frameworks — all indicators of a learning-oriented environment rather than a pure execution role.

The required 2–4 years of data engineering experience positions this as a mid-junior to mid-level role. Market benchmarks for Data Engineers with this stack in Brazil typically range from BRL 8,000–18,000/month depending on seniority and company size; a global insurer at this scale should be at the higher end.

• Watch for: The exclusivity clause prohibits side projects or parallel employment — a significant constraint for freelancers or those building personal ventures.
• Skills in demand: PySpark, AWS Glue, dimensional modeling, and data governance are top-tier skills for Data Engineer roles globally, boosting long-term career mobility.

Domain experience in regulated industries (insurance/financial services) is a valuable career differentiator, opening doors to fintech, banking, and enterprise data roles internationally.

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. Our Client is part of one of 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 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.

Required 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.

Technical Skills — Required

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

Technical Skills — Preferred

• AWS ecosystem experience
• 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.

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.

Is this role fully remote or does it require on-site presence in Brazil? The job posting does not explicitly specify remote or hybrid arrangements, but it requires legal authorization to work in Brazil. Candidates should clarify the work model (remote/hybrid/on-site) during the interview process. What level of experience is required for the Associate Data Engineer position? The role requires 4–6 years of total professional experience, with 2–4 years specifically in Data Engineering, Data Integration, or Analytics Engineering. A Bachelor's degree in a technical discipline is preferred. Does FBS sponsor work visas for this position in Brazil? No. The posting states that employment is conditional on the candidate having valid local legal authorization to work in the country where the role is based, and FBS does not sponsor or obtain work authorization unless explicitly stated. What is the technology stack used in this role? The required stack includes Python, AWS Glue, PySpark, SQL, Data Warehousing, Dimensional Modeling, and REST API Integration. Preferred skills include Dremio, Data Catalog technologies, and broader AWS ecosystem experience. What benefits are offered for this position? Benefits include a competitive salary with performance-based bonuses, private health insurance, a pension plan, paid time off, training and development, grocery vouchers, and saving funds (SGMM). Note that benefits vary by employee level.

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