Budva, Montenegro
I'm a Senior Software Developer with 13+ years of experience in full-stack development, specializing in building scalable systems and optimizing existing technologies. I've worked across a variety of industries including fintech, energy, and manufacturing, where I focused on driving innovation and improving efficiency. My core skills include .NET, C#, SQL, microservices architecture, and cloud technologies. I've successfully led projects that saved millions by implementing predictive analytics, optimizing system performance, and reducing operational costs. A recent highlight includes reducing payment routing errors by 80% in banking and saving $3M annually through predictive analytics in the energy sector. While my expertise is deeply rooted in system architecture and backend development, Iโm passionate about working on projects that require both technical mastery and creative problem-solving. My experience extends to working with modern tools and frameworks such as Kubernetes, Azure DevOps, RabbitMQ, and CI/CD pipelines, which I leverage to optimize deployments and enhance system performance. When I'm not coding, I'm passionate about staying on top of industry trends, whether thatโs in game development or emerging tech. I'm always looking for ways to apply my problem-solving skills to new challenges and am excited to collaborate with teams that value innovation and efficient solutions. If youโre looking for a developer who thrives in dynamic environments and is committed to delivering high-quality, scalable solutions, feel free to connect. Iโm always open to new opportunities and discussions on how we can innovate together. Email: [email protected] WhatsApp: https://wa.me/qr/E3WNH7AVC4IIN1 Telegram: https://t.me/han73r
POS System Migration Project - Replaced outdated POS system 2500 locations, optimizing message delivery between registers and reducing server load by 60%, enabling real-time transaction processing and reducing infrastructure costs. .NET, C#, Angular, Protobuf, Kubernets, Azure DevOps, REST API, RabbitMQ, MS SQL, LiteDB, PostrgreSQL, RavenDB, Microservices Modernized the Banking Transactions System Project - Halved the deployment time of the runtime environment by eliminating unused tests, caching dependencies, and optimizing the CI/CD pipeline. This enabled faster rollouts, decreased downtime, and improved team efficiency. - Developed a feature allowing users to select their preferred bank for incoming transfers directly in the app. Reduced error rates for misrouted payments by 80%, significantly cutting operational costs and enhancing user satisfaction.
Created a predictive analytics system to reduce transportation costs - Led a team of 5 developers to design and implement a predictive analytics system for optimizing tanker, rail, and fuel truck charters, utilizing advanced forecasting techniques. Achieved approximately $3M in annual savings by enhancing transportation planning and decision-making. - Transitioned monolith app to microservices, reducing data processing time from 4 minutes to <100 msec. Enabled real-time access for leadership, improved decision-making speed, and ensured 99.9% data accuracy. - Automated data collection from 20 departments, eliminating manual input and reducing data errors by 40%. Achieved a 30% reduction in analyst costs and enabled faster, more accurate decision-making. - Implemented CI/CD pipelines with Git, automating deployments and eliminating version discrepancies. This ensured zero manual errors and uninterrupted access to up-to-date systems for top management.
Enabled seamless data exchange between systems, reducing manual compliance checks - Developed services for seamless data exchange, enabling engineers to focus on development instead of manual data validation, reducing compliance checks by 40%. - Collaborated with solution stakeholders to gather requirements and deliver effective solutions with minimal delays, improving project efficiency by 30% and reducing costs by 20%. - Streamlined real-time data digitization and continuous data loading into databases, reducing data errors from 25% to 1%, improving data accuracy and processing efficiency.