My professional background and experience has centered around leading code implementations within project executions, interfacing with clients in order to understand their needs and requirements, as well as advancing data pipeline architectures, which are crucial for migrating data workloads to, as well as building AI applications within the Google Cloud Platform.

My contributions (from design to delivery) have enabled efficient and scalable data solutions, reducing infrastructure costs significantly. Within this dynamic environment, my proficiency in Data Engineering, AI, as well as knowledge of Machine learning Operations has been pivotal to successfully transitioning complex analytics workloads to cloud-based platforms.

As a former Mentor at Lighthouse Labs, I've imparted Data Science & Analytics expertise, guiding interns and shaping learning content for future data professionals. In keeping with the current developments in the AI space, I have gained an understanding of LLMs, Prompt Engineering, as well as have built and deployed a couple of prototype RAG applications on Google Cloud Vertex AI.

I enjoy working with data, discovering valuable insights that help solve problems for businesses and other types of organizations.

My commitment to excellence is reflected in how I contributed(and in some cases, led) team efforts to enhance the analytical capabilities of our clients. Through collaboration, we've overcome project challenges and delivered robust data modeling solutions, leveraging our expertise in data architecture and our strategic use of dbt and BigQuery with Airflow Orchestration, migrating of Hadoop workloads from On Prem to Google Cloud Platform, as well as Databricks Workflows for continuous integration and deployment.

This is a sampling of the work I have been doing for the past couple of years, since I made a major career pivot into Data Science. Programming and developing solutions within the data space has become my passion and pursuit. I place a high value on personal growth and making positive contributions in a friendly team environment, and I am looking to do just that to help organizations build and develop their data strategy.

• 👨‍💻 I'm currently a Senior Data Engineer at Badal.io, the foremost Canadian GCP consulting company.
• 👨‍💻 I used to be a Data Scientist and eventually, a Data Engineer at Totogi (A TelcoDR company).
• 👨‍🔬 On the side (after hours, casually) I help out as a Data Science Mentor with The Lighthouse Labs Data Bootcamp.
• 👨‍🔬 Before that, I was an Applied Machine Learning Specialist with ReVisionz Inc.
• 👨‍🔬 And Before that, I was a 2021 Data Science Fellow , and helped develop a Recommender System PoC model with Cybera Inc and Hockey AI(Actionable Insights).
• ☁ I have been learning and building AI Applications on various foundation models (LLMs). In addition, I am keeping up to date from time to time with various Learning programs, bootcamps, individual and team projects, internships and fellowships since late 2019.
• 👨‍🎓 Making this switch into Data Science and ultimately Data & AI Engineering has become the best career decision I have made.

• 🔭 I have been working on a very complex Data Migration Projects (lift-and-shift, refactoring and mordernization) on Google Cloud Platform, implementing data models and Data Warehousing designs using dbt and airflow with Google Cloud BigQuery, for a major Enterprise Banking Client in Canada. I have also been involved with the building of pipelines for Apache Hive lift-and-shift workloads with Python and HiveQL and shell scripting. This is high-end GCP consulting at its best!

• 🌱 I was working on Platform Configuration, Backend Development (Flask) and Telco Data Migration projects, implementing Telecom Charging Software Systems hosted on the Public Cloud (AWS)

• 🌱 I’m currently improving my cloud and Generative AI Engineering skills, working on picking up product development and prototyping skills with Product Faculty and AI Makerspace.

• 🌱 Previously, I was working on applying Computer Vision (Object Detection and Optical Character Recognition) models using the YOLO Object Detector and Microsoft Azure Cognitive Services. Models were used to extract technical information from industrial design documents and blueprints.

• 💬 Ask me about how to pivot into a tech career

• 📫 How to reach me: linkedin.com/in/ovokpus

• 😄 Pronouns: He/Him

• ⚡ Fun fact: I still have not yet seen "Star Wars"! Maybe someday, don't hold your breath! -

You can find my professional certifications in Credly and also in Accredible

My all time favorites are linked below in the Pinned Repositories. But here are others as well:

1. Retrieval-Augmented Generative AI Q&A Solution for Food Safety
2. Python-Azure-AI-REST-APIs
3. Text Summarizer Flask Application
4. Tensorflow BERT Sentiment Classifier
5. OpenAI Chat Application Deployed with Vercel
6. Chainlit Chatbot Application deployed with Huggingface
7. Collaborative Filtering Recommender Engine
8. Income Prediction Pipeline - MLOps
9. My MLOps Learning Repository
10. Azure AI Engineering Code Library
11. Azure Machine Learning Project
12. Employee Attrition Predictor

1. AWS ETL Pipeline
2. Azure Streaming Pipeline
3. Apache Airflow ETL
4. Document Streaming App with fastAPI, Kafka, Spark & MongoDB
5. Analytics Engineering Prototype with dbt and BigQuery
6. Contact Tracing using Elasticsearch and Streamlit Frontend
7. Time Series Analytics Pipeline with Python, InfluxDB and Grafana
8. Data Engineering with Hadoop - A Learning Project
9. Airflow Learning Project - Astronomer
10. Spark Application in Java

1. Salary Prediction Prototype
2. Car Manufacturing Test
3. Customer Segmentation using RFM modelling and K-Means Clustering
4. And here is my Business Intelligence Gallery

1. US Cities API Backend
2. News Frontend Application - React
3. Deploying Google Cloud Applications with Terraform
4. Application Deployment with Google Kubernetes Engine(GKE)
5. GKE Multi-Tenant Cluster Management with Terraform Implementation Playbook