Hello! I'm David Mugisha, a Senior Data Engineer with 7+ years of experience building scalable data solutions for intelligent products across aerospace, energy, and technology sectors. My passion lies in leveraging advanced analytics, cloud technologies, and artificial intelligence to solve complex business challenges and drive data-driven decision making.

• Intelligent WriteBack System: An AI-powered automated system at Collective[i] that captures and updates CRM data from emails and meetings, processing 1800+ events per day per worker and eliminating manual data entry.
• Real-time Microservice Platform: Built fault-tolerant systems processing 50+ messages/second with consistent updates across Salesforce and HubSpot using Kafka data pipelines.
• Scalable Data Architectures: Designing and implementing distributed computing systems that process 1000+ GB datasets with optimal performance.

I'm constantly exploring cutting-edge technologies and methodologies. Currently, I am diving deep into:

• Advanced MLOps: Enhancing machine learning model deployment and monitoring in production environments, see mlflow on miniio, mlops on databricks
• Real-time Analytics: Mastering streaming data processing and event-driven architectures.
• Cloud-Native Solutions: Exploring serverless architectures (see etl with azure functions) and containerized data processing on Kubernetes.
• Software Engineering Patterns: Mastering craftsmanship through architectural patterns like Domain-Driven Design (DDD), CQRS, Event Sourcing, and clean architecture principles. See e-commerce-allocation
• Data Engineering: Spark ETL Application with OOP practices in sales-processor
• AI Integration: Exploring implementing artificial intelligence in data engineering workflows for intelligent automation.

I'm always looking for opportunities to collaborate on open-source projects, especially those involving:

• Large-scale data processing and analytics platforms.
• AI-powered automation systems and intelligent data pipelines.
• Cloud-native data engineering solutions.
• MLOps and machine learning infrastructure.
• Software architecture and design patterns for scalable systems.

Feel free to reach out to me for discussions about:

• Data engineering best practices and scalable architectures.
• Real-time data processing and streaming analytics.
• AI integration in data pipelines and intelligent automation.
• Cloud technologies and distributed computing systems.
• MLOps and machine learning in production environments.
• Software engineering patterns and architectural design principles.

• LinkedIn: David Mugisha

He/Him

When I'm not architecting data pipelines, you might find me exploring ... countries, I love travelling. I also enjoy teaching - I've been an instructor at Octo Academy teaching Data Engineering and MLOps to technical professionals! Last but not least, I love dancing

• AWS Certified Data Engineer – Associate
• AWS Certified Solutions Architect – Associate
• Microsoft Certified: Azure AI Fundamentals, Data Engineer Associate, Data Scientist Associate
• Academic Excellence: National Mathematics Champion (Burundi) and multiple merit-based awards
• Research Publication: Published work on User-in-the-loop adaptive intent detection at ACM Conference
• Hackathon Winner: 'Coup de coeur' Prize for innovative IoT solution design

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