Data Engineer

The candidate is a highly skilled Data Engineer and Platform Engineer with extensive experience in developing and implementing ETL pipelines, optimizing data workflows, and leveraging cloud platforms to drive system efficiency and scalability. They excel in designing robust data models, automating manual processes, and conducting performance analyses to improve accuracy and reliability in data-driven environments.

Key accomplishments include building ETL pipelines capable of ingesting large datasets, enabling faster MI reporting, and automating workflows that saved significant manual effort and costs. They have a strong background in data deduplication, reducing redundant hits in screening systems, and performing comprehensive performance testing to guide superior system selection.

With expertise in Azure Data Factory, Databricks, Delta Lake, and other Azure services, the candidate has successfully optimized alert systems, reduced false positives, and implemented AML solutions to meet legal and regulatory requirements. They have developed scalable data pipelines and designed efficient data-loading mechanisms into data warehouses, ensuring seamless integration and analysis.

The candidate also brings leadership experience, having managed teams to ensure consistency in data workflows, spearheaded proof-of-concept initiatives, and implemented automated ticketing solutions to improve team productivity. Their technical proficiency spans Unix scripting, Actimize configuration, REST APIs, and advanced UI/UX development, ensuring end-to-end delivery of high-quality solutions.

Their ability to analyze complex datasets, optimize system configurations, and align technical solutions with business goals has enabled them to make impactful contributions across multiple projects in compliance, data engineering, and software development. The candidate is a proactive problem-solver and an adaptable team player with a demonstrated track record of delivering innovative solutions in dynamic environments.