Acerca de Sergiy
I help manufacturing and industrial companies turn raw data into real business value using Azure, IoT, and AI.
With 15+ years in software development and cloud solutions, I specialize in building scalable data platforms that improve production visibility, reduce downtime, and enable smarter decision-making.
What I can help you with:
• Design and implementation of Azure-based data platforms
• IoT data ingestion and real-time processing
• Building data pipelines (ETL, streaming, analytics)
• Industrial analytics and performance monitoring
• Preparing data for AI and predictive maintenance
Typical results my clients achieve:
• Better visibility of production processes
• Reduced operational downtime
• Faster and more reliable decision-making
• Scalable data infrastructure ready for AI
Tech stack:
Microsoft Azure, IoT Hub, Data Engineering, ETL, Cloud Architecture
Inglés
Bilingüe o nativo
Español
Competencia profesional básica
Acepta trabajo presencial
Barcelona (hasta 50 km)
Experiencia
- NetAI SoftwareIndustrial IoT & AI ConsultantENERGÍAoctubre de 2024 - Hoy (1 año y 9 meses)Barcelona, EspañaI help manufacturing and industrial companies improve production visibility, reduce downtime, and make better decisions using IoT, data and AI.Key areas I work on:• Production analytics platforms (real-time dashboards, OEE tracking)• Azure IoT data pipelines and cloud architecture• Industrial data integration and monitoring systems• Predictive maintenance and anomaly detectionI focus on delivering business impact, not just technology:• improving operational efficiency• reducing machine downtime• enabling real-time insightsTechnologies:Azure, .NET, IoT, Data Analytics, Cloud Architecture
- Manufacturing CompanyProduction Monitoring & IoT Analytics SystemQUÍMICAfebrero de 2021 - octubre de 2024 (3 años y 8 meses)Barcelona, EspañaDesigned and implemented a production monitoring and analytics system for a manufacturing company using IoT and Azure.Key results:• Enabled real-time visibility of production metrics across machines• Improved tracking of downtime and operational performance• Built dashboards for KPI and OEE monitoring• Integrated multiple data sources into a unified analytics platformTechnical scope:• IoT data collection and processing• Azure-based data pipelines and storage• Real-time dashboards and reporting• Scalable cloud architectureOutcome:Improved decision-making and operational transparency across production processes.
- Manufacturing CompanyAzure IoT Data Pipeline for Industrial Analyticsmayo de 2017 - febrero de 2021 (3 años y 9 meses)Designed and implemented a scalable Azure IoT data pipeline for industrial analytics and real-time monitoring.Key results:• Enabled reliable ingestion of high-volume IoT data from industrial equipment• Built a centralized data platform for analytics and reporting• Improved data availability and processing speed for operational insights• Provided a foundation for advanced analytics and predictive use casesTechnical scope:• Azure IoT Hub for device connectivity and data ingestion• Stream processing and data transformation pipelines• Cloud-based storage and data architecture• Integration with analytics and dashboarding toolsOutcome:Delivered a robust and scalable data infrastructure that allowed the company to leverage industrial data for monitoring, optimization, and future AI-driven analytics.
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Formación
- Doctor (PhD)Kharkiv National University2006Computer Science / Software Engineering with focus on distributed systems, data processing and backend development.