Crafting Comprehensive Strategy for Data Infrastructure

Impact generated #MultiCloudStrategy #DataInfrastructure #CostEfficiency #CloudIntegration #DataScalability #FutureProofing #TechnologyStrategy #DataMesh

Project developed under the guidance of the company’s CTO alongside other departments in the technology area. This multi-year initiative, supported by insights from Gartner and in collaboration with global technology providers such as Google, AWS, Microsoft, and Databricks. 

The project had two main goals: Future-proof the company's big data infrastructure and addressing data processing, storing and operational costs. By diversifying and integrating existing on-premises infrastructure with multiple cloud environments, it aims to create a multi-cloud, multi-tenant data mesh that would meet rapidly expanding data demands.

My responsibilities included defining strategic objectives for the analytical data, structured and unstructured, overseeing the creation of a comprehensive technical roadmap, coordinating our strategic partners, and guiding my teams through the development of an MVP designed to establish clear performance baselines. I facilitated cooperation between internal stakeholders and external partners, ensuring alignment on key issues such as data integration, scalability, cost management, and vendor pricing strategies. This strategic alignment was essential for minimizing future costs as data collection and transformation needs continue to grow exponentially.

Through scenario simulations, detailed performance testing, and defining clear success metrics, a robust MVP was built, representing a framework capable of scaling efficiently, controlling operational expenses, and supporting sustained growth. Although the full realization of the strategy extends beyond my tenure, this initiative set the foundation for cost-effective, scalable, and resilient big data infrastructure that supports long-term innovation and strategic advantage.