Moyosore O. Lawal

Results-driven Data Architect and Engineering Leader with over 15 years of experience designing and delivering scalable data platforms, advanced analytics pipelines, and enterprise architectures across healthcare, finance, insurance, and manufacturing. Proven expertise in cloud-native data solutions (AWS, Snowflake, Databricks), modern ETL/ELT frameworks, data governance, and interoperability and security standards (OMOP, HL7, PCIDSS). Notable achievements include: Built real-time and event-driven data pipelines powering statewide healthcare dashboards, predictive analytics platforms, and de-identified research repositories. Led end-to-end delivery of data strategies for clients, from roadmap definition to scalable implementation, enabling AI/ML workloads, compliance, and self-service analytics. Migrated and modernized legacy pipelines using PySpark and AWS tools, reducing costs and improving data throughput and reliability. Architected microservice-based platforms supporting machine learning APIs, customer experience solutions, and ROI forecasting models. Mentored and led cross-functional teams, fostering a high-performance culture grounded in data quality, reusability, and business alignment. Deep technical fluency in modern technical skills with a consistent track record of translating complex business needs into actionable, high-impact data solutions.

Agile Chief Systems Architect with [Number] years spent enhancing existing layouts as well as designing complete enterprise-class system architectures from ground up. Brings multi-national portfolio of successful system infrastructure designs to bear on every project. Employs vast technical skills in cloud-based architecture and database technologies to provide optimal architecture outcomes to scale and on time.

• Built real-time and event-driven data pipelines powering statewide healthcare dashboards, predictive analytics platforms, and de-identified research repositories.
• Led end-to-end delivery of data strategies for clients, from roadmap definition to scalable implementation, enabling AI/ML workloads, compliance, and self-service analytics.
• Migrated and modernized legacy pipelines using PySpark and AWS tools, reducing costs and improving data throughput and reliability.
• Architected microservice-based platforms supporting machine learning APIs, customer experience solutions, and ROI forecasting models.
• Mentored and led cross-functional teams, fostering a high-performance culture grounded in data quality, reusability, and business alignment.