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Hi, I’m Damola 👋

Data Engineer | AI Engineer | Data Analyst | Cloud & AI Practitioner

I build reliable data systems from ELT pipelines and cloud migrations to backend services and analytics layers. My work focuses on turning fragmented data into scalable, production-ready platforms, with a growing emphasis on LLMs and Generative AI in real-world workflows.


🛠️ What I Work On

  • Data Infrastructure: Designing and maintaining robust ELT/data pipelines.
  • Cloud Strategy: Leading cloud migrations and building modern data platforms.
  • AI Implementation: Integrating LLMs and GenAI (RAG, Agentic AI) into production environments.
  • Software Engineering: Developing backend services, REST APIs, and internal tooling.
  • Business Intelligence: Creating dashboards and reporting layers that bridge the gap between data and strategy.

👩‍💻 Tech Stack

Category Tools & Technologies
Languages Python · SQL · JavaScript · AppScripts
Data Engineering ELT pipelines · Data modeling · Orchestration · APIs · Data quality & monitoring
Cloud & DevOps Cloud Data Warehouses · Object Storage · Containers · CI/CD
LLMs / GenAI Agentic AI · Prompt engineering · RAG · Model integration · Evaluation
Backend Dev Flask · FastAPI · REST APIs · Auth · Background jobs
Analytics & BI Power BI · Excel · Google Sheets · Dashboard design · Stakeholder reporting

🚀 Projects & Experience

  • Data Platform & ELT Pipelines: Architected private, high-scale data platforms and ELT workflows.
  • Cloud Migrations: Led initiatives to transition legacy systems to modern cloud environments.
  • LLM-powered Tools: Built and deployed internal AI tools, focusing on production-grade reliability.
  • Open Source: My public repositories focus on architecture patterns, specialized tooling, and public data projects.

📊 Data Philosophy

I care about clarity and usability as much as correctness. I build data products that non-technical users can actually trust and use to drive value.

  • Scalability: Simple systems scale better.
  • Fundamentals: Good data models matter more than flashy tools.
  • AI Integration: LLMs are components, not products.
  • Efficiency: Cost is a feature, not an afterthought.

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