Own full project lifecycles for high-stakes, multi-million dollar Real-Time Payments processing platforms for major Tier-1 US Banking institutions. Oversee resource allocation, build detailed end-to-end execution plans, manage cross-functional dependencies, and track financial project expenses to deliver timely financial reporting to stakeholders. Serve as the primary point of contact for enterprise clients, owning executive status updates, risk communication, and change management. Partner closely with internal Product/R&D, QA, and Delivery teams to maintain strict execution quality and adhere to core uptime and data integrity SLAs.

Designed and implemented GCP-based scalable enterprise big data solutions and pipelines for global Telco and Banking accounts. Managed data quality gaps and scaling risks over pipelines processing terabytes of transactional data daily, upholding strict data reliability metrics. Collaborated directly with Data Science and Engineering teams to deploy production ML models into production environments while ensuring optimization of consumption costs.

Led the end-to-end implementation and migration of mission-critical legacy core banking software to modern cloud-based architectures for leading financial institutions. Managed and mentored cross-functional engineering teams of 15+ specialists across multiple concurrent development tracks, keeping milestones strictly on time and in scope. Acted as a strategic partner to local banking leadership teams, navigating scope changes, resource planning, and resolving complex technical blockers.

Directed massive GCP migration strategies and AI/ML data initiatives for top-tier Telecommunications and Banking clients. Successfully orchestrated a 6-month migration of an enterprise Telco Data Warehouse from complex on-premise environments to GCP, unblocking high-volume analytical performance. Managed technical risks tied to changing source data volumes and legacy system interdependencies during Cloudera-to-GCP data migrations for global banking clients. Leveraged early automated ML pipelines and automated frameworks to accelerate internal tracking, data mapping reviews, and stakeholder progress reporting.

Architected a serverless PySpark customer micro-segmentation data platform processing millions of high-value transactional records monthly for three major retail banks. Designed automated cloud infrastructure scaling utilizing Terraform and AWS Step Functions, drastically reducing processing latency and operational errors.

Designed and delivered enterprise-scale Data Lake and automation solutions for high-value clients across the Banking, Telco, and Manufacturing sectors. Acted as the lead strategic architect for Big Data operations processing petabytes of structured/unstructured data, focusing directly on engineering quality and infrastructure cost optimization. Led and mentored technical teams of 20+ engineers.