Fortune Mogoeng

Led the design of an enterprise data and AI architecture strategy, migrating legacy on-prem core banking databases to an Azure cloud landing zone with an organisation-wide reference architecture. Built a cost-optimised modern data platform (Azure Databricks, Azure Synapse) and established governance, master data, and metadata standards to maintain SOC2/PCI-DSS audit readiness.

Designed and governed multi-source ETL/ELT data architectures across AWS and Azure, ensuring strict enterprise SLAs and data quality standards for high-volume transaction log environments. Orchestrated production workloads using EKS and Docker, and applied Terraform-based Infrastructure-as-Code to enable reproducible deployments.

Modernised legacy SQL Server systems by migrating them into production-ready automated AWS cloud data pipelines using Python, PySpark, and Terraform IaC. Implemented enterprise governance controls, data integrity validation frameworks, and security/regulatory audit support while improving downstream analytics pipeline throughput.

Spearheaded AWS infrastructure modernisation by migrating legacy high-latency SQL Server systems into automated cloud data pipelines using Python and PySpark. Implemented governance controls and data integrity validation frameworks, authored enterprise architecture and integration documentation, and improved pipeline throughput for downstream analytics.

Coordinated with distributed agile teams on automated pipeline execution and continuous integration testing, supporting reproducible cloud architecture documentation on AWS. Contributed to data quality frameworks and translated technical findings into stakeholder-ready insights.

Delivered automated data infrastructure and ELT ingestion architectures for international clients, including relational schema design for large-scale data warehousing environments. Documented integration patterns to support downstream consumption and reuse.

Delivered automated data infrastructure and ELT ingestion architectures for international clients, including relational schema design to optimise large-scale data warehousing environments. Documented integration patterns to enable downstream reuse and operational clarity.

Partnered with tier-one banking and wealth-management clients to scope, architect, and deliver custom data reporting configurations and warehouse solutions across AWS and Azure. Performed data validation testing and post-deployment troubleshooting to resolve data quality anomalies before major production rollouts.

Earned a Bachelor of Information Systems (Information Technology). Coursework covered database architecture, business systems analysis, Python programming, and data visualisation.

Completed an SQL certification course covering SQL fundamentals and related querying concepts.

Completed an Advanced Excel certification course focused on advanced spreadsheet skills.

Completed a Data Engineering Certificate (NQF 5) with Sand Technologies.

Completed a Power BI certification course focused on building dashboards and enterprise semantic layer design.

Activities and societies: Core focus included Database Architecture, Business Systems Analysis, Python Programming, and Data Visualisation.

Earned a Bachelor of Information Systems (Information Technology). Focused on database architecture, business systems analysis, Python programming, and data visualisation.

Completed Udemy certifications in SQL and Advanced Excel.

Earned a Claude AI Verification certification focused on AI tooling for scripting, documentation, and architecture optimisation.