Description
Our Client, a leading US insurer, serves over 10 million households with 19 million policies across 50 states through 48,000 agents and 18,500 employees.
The Life Data Platform (LDP) & Data Enablement team acquires, integrates, governs, models, and publishes enterprise data across on-premises and cloud platforms, enabling trusted data products, analytics, and operational insights for Life Insurance functions.
As a Data Engineer, you will design, develop, and support scalable data pipelines, data models, and enterprise data products driving reporting, analytics, and business capabilities. You will work closely with stakeholders to deliver high-quality data solutions and establish a trusted source of enterprise data.
Key Responsibilities:
- Design and develop scalable data pipelines and 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 them 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
- 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
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