Natallia Laurova
Principal Data Engineer @SageSure
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WORK HISTORY
Principal Data Engineer @SageSure
As Principal Data Engineer at SageSure, I design and build scalable, metadata-driven data pipelines on AWS that power analytics, reporting, and risk modeling across the business.My work spans the full data engineering lifecycle — from modernizing legacy ETL systems to delivering production-grade infrastructure that handles large volumes of structured and semi-structured data (XML, JSON) at scale.Key contributions include:• Built end-to-end ingestion and transformation pipelines using AWS Glue, S3, Redshift, and Athena, integrating data from vendor systems, AWS DMS, and event-driven sources (SQS)• Led the design and implementation of cross-account Redshift Data Sharing, enabling near real-time data access across multiple departments while improving governance through IAM Identity Center and Lake Formation — eliminating individual DB user management entirely• Implemented centralized logging and monitoring in Redshift, enabling partition-level tracking, failure recovery, and operational transparency across pipelines• Standardized development practices by introducing reusable AWS Glue job templates, CI/CD workflows, and infrastructure-as-code via Terraform• Resolved complex schema consistency challenges and designed flexible data models capable of adapting to schema drift across disparate source systems• Supported data governance initiatives including role-based access patterns and integration with Alation
EDUCATION
Belarusian State University of Informatics and Radioelectronics
Bachelor's degree, Computer Engineering
Belarusian State University of Informatics and Radioelectronics
Master's degree, Computer Science
ABOUT NATALLIA LAUROVA
Big Data Engineer with experience in AWS cloud and on-prem systems design and implementation. Experience with AWS, Hadoop, Hive, Spark and Bash. Able to use Spark Data Frame and Data Set from Spark SQL API for data processing. Fine-tuned resources for long-running Spark applications to utilize better parallelism and executor memory for more caching.
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