Joshua Abiodun-Olojede Email & Phone Number

United Kingdom

Pioneered automation initiatives, particularly in Database migration (Liquibase) and CI/CD (Azure DevOps), resulting in a significant reduction in manual efforts and over 50% improvement in operational efficiency and security.Led multi-cloud infrastructure management on AWS and Azure, optimizing resource utilization, implementing load balancing, auto-scaling, and robust monitoring, while enhancing security by 50%.Configured and optimized NGINX and Apache web servers, specializing in the delivery of both static and dynamic content thus increasing reliability by over 50%.Authored and automated AWS CloudFormation templates, increasing deployment speed and accuracy by over 80% across the development, staging, and production environments.Engineered advanced CI/CD pipelines, skillfully integrating secrets management to streamline the build and deployment processes for mobile applications and APIs thus reducing deployment time by 60%.

United Kingdom

Designed and deployed a robust Delta Live Tables pipeline on Databricks, improving data accuracy by 30% through an Autoloader and reducing processing time by 50% across the Medallion architecture.Streamlined CI processes on Databricks with CircleCI, reducing deployment time by over 50% and increasing development team efficiency by 60%.Engineered dynamic environmental configurations on Databricks, reducing configuration errors by 40% and enhancing environment consistency across workspaces.Developed an AWS Step Functions workflow that uses EMR and Spark to process massive data, resulting in a 30% reduction in processing costs and an over 50% improvement in job execution times.Implemented real-time streaming via Azure Event Hubs and Azure Functions as API, connecting to Facebook webhooks, which decreased data latency by 25% and significantly enhanced real-time data processing capacity by 50%.

Texas, United States

Supported Kubeflow development and data aggregation efforts, enhancing efficiency by 20%. Collaborated with a team of 10 individuals to implement MLOps Pipelines, and Feature Store for Machine learning, Model deployment and Model Serving.Introduced Agile sprint development and deployment cycles, halving project timelines and enhancing project delivery speed by 50%.Orchestrated ML and DL workflows using Argo Workflows and Couler, and employed Kubeflow on Kubernetes for streamlined ML pipeline deployment, improving deployment accuracy to about 50%.Enforced best practices in backend development, optimizing API design with FastAPI, streamlining database management through Alembic, and orchestrating high-performance web services with Starlette and Uvicorn, resulting in a remarkable 50% reduction in project completion time.

Nigeria

Collaborated with a 10-member team to develop custom applications, improve decision-making processes, and implement optimization algorithms, resulting in a 60% increase in predictive accuracy and efficiency.Introduced advanced graphic visualization techniques, simplifying data-heavy reports and enhancing data analysis by 30%.Performed data preprocessing to align raw data with machine learning algorithm assumptions, resulting in a remarkable 70% reduction in training loss.Expertly planned and executed MLOps pipelines, improving model serving efficiency by 40% and ensuring comprehensive model monitoring for enhanced model accuracy and reliability.Established and maintained a robust knowledge base and documentation repository, reducing onboarding time for new team members by 60% and fostering seamless knowledge sharing across projects.