Over a decade designing and deploying enterprise data estates across GCP, AWS and Azure. As a former Google senior engineer and now a PwC Senior Manager, I lead the migration of mission-critical workloads into the cloud with a focus on 99.99% reliability, security compliance and production-grade MLOps.
I move fluently across real-time streaming, lakehouse architecture and infrastructure-as-code: Dataflow, Pub/Sub, Kinesis, Databricks, Terraform and Kubernetes, with deep roots in Python, Java, Scala and SQL. What I care about is the part most teams skip: turning messy, contested, high-volume data into systems that stakeholders actually trust.
Today I lead cloud, data and AI engineering at PwC Canada, translating hard technical strategy into delivery that clears audit, scales, and holds up in production.
Anyone can move data. The work is making an organisation agree on what it means, and then keeping that true at scale.
Operating principles
The expensive mistakes are made in the first week, not the last sprint.
A pipeline nobody believes is a pipeline nobody uses. Quality and lineage are features.
Fewer moving parts, sharper contracts, and boring infrastructure that survives handover.
I can defend a design to staff engineers and explain the trade-off to the board.
Certifications
Google Cloud
Amazon Web Services
Microsoft
Databricks
Neo4j
Simplilearn
Education
Completed March 2024
Applied MSc, Data Engineering for Artificial Intelligence
Paris, France
Completed October 2014
BEng, Electronics and Computer Engineering
Nigeria