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dilshapamuditha

Dilsha P

@dilshapamuditha

Software Engineer

Sri Lanka
Englisch, Singhalesische Sprache
Einige Informationen werden in englischer Sprache angezeigt.
Über mich
I am a motivated and passionate Associate Software Engineer with over a year of hands-on experience in software development, specializing in full-stack solutions using .NET, C#, and SQL. My experience spans across multiple industries, working on projects from POS systems to automation apps. I have a strong background in API development, mobile solutions, and data analysis.... Mehr lesen

Kompetenzen

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dilshapamuditha
Dilsha P
offline • 
Durchschnittliche Antwortzeit: 1 Stunde

Meine Dienstleistungen

API & Integrationen
I will develop asp net core web API, rest API, and backend systems
Ab50 $ / ProjektWeitere Details

Arbeitserfahrung

Vertexo

Software Engineer

Vertexo • Vollzeit

Jun 2024 - Present • 2 yrs 1 mo

International Collaboration: Direct technical lead for **foreign client accounts**, reducing requirement-todeployment time by 20% through agile consultation. Enterprise Ecosystem: Architected a multi-platform POS system currently serving **300+ branches**, ensuring 99.9% data consistency across web and mobile. • System Migration: Successfully migrated legacy VB6 applications to **.NET Core**, resulting in a 40% increase in system processing speed and reduced maintenance costs. Hybrid Data Access: Optimized high-performance reporting using **ADO.NET**, reducing complex query execution time by 50%.

AppMap

Associate Software Engineer

AppMap • Vollzeit

Oct 2023 - Jun 2024 • 8 mos

POS Development: Developed a robust POS and Employee Management System that automated payroll for **100+ employees**, reducing manual entry errors by 30%. Architecture: Designed optimized business logic layers and automated SQL-based reporting modules, improving decision-making speed for management.

Product Associate

Innova • Vollzeit

Oct 2021 - Oct 2023 • 2 yrs

• Process Automation: Engineered **Python-based automation scripts** that reduced manual data processing time by 60%, handling thousands of XML/HTML files daily. • Machine Learning: Implemented ML-based classification tasks that improved data accuracy by 15% compared to manual oversight.