Fred Mojekwu

A passionate cloud Data Engineer with experience in designing and delivering scalable data platforms across Azure and AWS. Skilled in building end-to-end data pipelines (ETL/ELT), data lakehouse and warehouse solutions, and enabling analytics and machine learning through well-structured, governed data. I specialize in: Cloud Data Engineering: Azure Data Factory, Synapse, Databricks, Microsoft Fabric and Power BI. Data Architecture & Modeling: Dimensional models (star/snowflake), Kimball/Inmon, Delta Lake. DevOps & Automation: CI/CD pipelines, Git, GitHub Actions, Terraform, Docker, ARM templates Data Integration: APIs, SQL Server, PostgreSQL, MongoDB, Cosmos DB, JSON, and Parquet. Analytics & ML Enablement: Power BI (DAX, Power Query), Python (Pandas, PySpark), ML-ready pipelines in finance & energy projects I’m passionate about solving complex data challenges, optimizing pipelines for performance and scalability, and ensuring data quality, security, and governance at every stage. My recent projects include building ML-enabled pipelines for stock market prediction and automating regulatory reporting workflows for the Ontario Energy Board (Auto IR project).