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Mid-level data engineer, metro location, and broad AWS-data skillset create high candidate competition.
Role prefers insurance/reinsurance domain expertise, so industry background strongly influences fit.
Explicit 5+ years plus mandatory AWS data platform and governance skills makes shortlisting strict.
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Design and maintain canonical data models and scalable data pipelines supporting contracts, transactions, billing, cessions, treaties, and reporting in an AWS-native reinsurance platform.
Implement and manage event-driven data processing frameworks ensuring data quality, auditability, and lineage across multiple enterprise systems including policy administration and finance.
Build and support operational and analytical data structures, CI/CD pipelines, and enable AI readiness through metadata enrichment and searchable datasets.
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field.
5+ years of Data Engineering experience, with demonstrated AWS cloud-native data solutions expertise.
Strong proficiency with AWS services including S3, Glue, Lambda, Redshift, EventBridge, SNS, SQS, Step Functions, and related data governance tools.
Technical skills in Python, SQL, and experience with databases like PostgreSQL/Aurora, DynamoDB, and Redshift.
Experienced data engineer with hands-on expertise in AWS cloud data engineering and event-driven architectures within insurance/reinsurance domains.
Familiar with designing scalable, production-grade data platforms handling complex financial and policy data such as treaties, cessions, billing, and settlements.
Skilled in implementing strong data governance, lineage, and audit controls to support enterprise-grade reporting, analytics, and AI capabilities.