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Role Overview:
A Data Engineer in the insurance industry is responsible for designing, building, and maintaining data pipelines and systems to support the organization’s data infrastructure.
The role involves collecting, processing, and transforming data from various sources to ensure it is accurate, accessible, and ready for analysis.
This enables teams to make data-driven decisions, improve risk assessment, underwriting, and claims management.
Key Responsibilities:
• Design, build, and manage scalable data pipelines to collect data from different sources (e.g., CRM systems, claims, policy administration).
• Develop and maintain ETL (Extract, Transform, Load) processes.
• Collaborate with data scientists and analysts to provide clean, structured data for predictive models, fraud detection, and reporting.
• Ensure data integrity, security, and accessibility in compliance with industry standards and regulations like HIPAA or GDPR.
• Work closely with business units to understand data needs and translate them into technical solutions.
• Optimize performance of data warehouses and cloud data solutions (AWS, Azure, GCP).
• Implement data governance and quality assurance measures.
• Stay updated with emerging technologies in big data and cloud storage.
Skills Required:
• Proficiency in SQL, Python, and big data tools (e.g., Hadoop, Spark).
• Experience with cloud platforms (AWS, GCP, Azure) for data engineering.
• Familiarity with data integration and ETL tools (e.g., Apache NiFi, Talend).
• Knowledge of insurance-specific data types like claims, underwriting, and policy data.
• Strong understanding of data governance, security protocols, and compliance standards.
• Experience with data modeling, database design, and performance tuning.
Education & Experience:
• Bachelor's degree in Computer Science, Data Science, or related field.
• 3+ years of experience in data engineering or a related field, preferably in the insurance industry.
Job Type: Contract
Contract length: 12 months
