Architected and led development of a large-scale data analytics
platform using Node.js, enabling secure data processing through
mirrored client environments, eliminating direct access
requirements while maintaining data integrity.
Designed and implemented ETL pipelines in Python for various
data sources, with particular focus on SAP systems, creating
synchronized MSSQL databases and data repositories that enabled
real-time analytics operations and reporting.
Built and maintained diverse analytics solutions combining
Python, MSSQL, and visualization tools to help clients derive
actionable insights from complex ERP data, improving their
decision-making capabilities.
Developed custom machine learning models for OCR document
processing, creating an automated solution for contract analysis
that significantly improved data extraction efficiency.
Assessed and provided strategic recommendations for enterprise
data architecture, notably for a major banking client's data
warehouse implementation to enable automated analytics
capabilities.