DATA ENGINEER & AI PRACTITIONER
Emmanuel Onwubuya
Building robust data pipelines and AI-driven solutions that power modern businesses.
Learn more about me
Building robust data pipelines and AI-driven solutions that power modern businesses.
Learn more about me
High-impact Data Engineer with 4+ years of experience building scalable data pipelines, designing resilient data models, and leading cloud-based data platform migrations. Adept at translating complex business needs into robust, production-grade data solutions that power analytics, machine learning and real-time decision-making.
Skilled in Python, SQL and Spark, with hands-on experience using tools and platforms such as dbt, Databricks, Airflow and Terraform. Deep understanding of data modeling, orchestration, CI/CD and cloud infrastructure (AWS, Azure, GCP).
Passionate about building innovative AI applications that solve real-world problems. Currently developing cutting-edge projects including Ufindar - an AI-powered university search tool using LangChain and semantic search, and Ginja App - a revolutionary productivity platform that will transform how businesses and individuals interact with artificial intelligence technology. These projects showcase my expertise in applying LLMs and AI to create practical, user-friendly solutions that bridge the gap between complex AI capabilities and everyday usability.
Known for improving pipeline performance, ensuring data integrity and bridging technical depth with business context to deliver measurable impact. I thrive on transforming complex AI concepts into accessible, production-ready applications that drive business value.
4+ years building scalable pipelines and data platforms.
Building Ufindar, Ginja App, and innovative AI solutions.
Expert in AWS, Azure, GCP, and modern data stacks.
Transforming complex AI concepts into user-friendly applications.
A comprehensive toolkit built through years of hands-on experience in data engineering and AI.
Leading cloud-based data platform migrations and building scalable data pipelines for Healthcare Media services. Implementing modern data engineering practices with focus on data quality and real-time analytics. Successfully reduced data processing time by 60% and improved system reliability to 99.9% uptime.
Partnered with Airbus on Manufacturing Engineering projects to design and implement scalable data pipelines and resilient data models. Developed front-end applications to track aircraft production stages, integrated client APIs for data extraction, and built ETL workflows using PySpark and Docker. Leveraged Skywise and Palantir platforms with PostgreSQL to ensure data quality, optimize transformations, and support real-time decision-making in production environments.
Built foundational data pipelines and contributed to data infrastructure improvements for real estate analytics platform. Gained hands-on experience with cloud platforms and modern data engineering tools. Successfully implemented ETL processes that processed 1M+ property records daily, improving data accuracy by 35% and reducing manual processing time by 80%.
Innovative solutions showcasing expertise in data engineering and AI applications
Natural-language university search engine that uses LangChain and Supabase with embedding-based semantic search. Allows users to find universities via conversational queries; backend built with Python and deployed as a live prototype.
Ready to discuss data engineering opportunities or collaborate on innovative projects.
I'm always interested in discussing new opportunities, innovative projects, or collaborating on data engineering and AI initiatives. Let's connect!
emyraeleson@gmail.com
github.com/Emyrael
Emmanuel-Onwubuya