Ismail D. Wakilu

Designed and implemented secure, scalable data platforms on AWS and Snowflake, leveraging dbt to increase data processing efficiency by 30%. Mentored and managed a team of junior engineers, embedding CI/CD pipelines, TDD, and Agile methodologies, improving team productivity and skill development. Architected Medallion architecture with schema evolution, ensuring data quality and enabling scalable data lake solutions. Partnered with business and operations teams to develop high-quality data products aligned with regulatory requirements, driving actionable insights across the organization. Improved deployment reliability and reduced costs by adhering to AWS Well-Architected Framework and governance practices.

Architected fault-tolerant data pipelines using AWS services (Lambda, Glue, Step Functions), processing 5TB+ daily data while maintaining sub-minute latency. Collaborated with cross-functional teams to implement cost-optimization strategies, reducing AWS operational costs by 20%. Designed and deployed automated data quality frameworks, reducing data errors by 75%. Enhanced query performance by 25% through optimized data modelling and partitioning. Established real-time monitoring using AWS CloudWatch and X‑Ray, achieving 99.9% uptime.

Designed and deployed AWS-based data infrastructure, including Redshift, EMR, and Glue, enabling high-volume analytics in the banking sector. Built automated data quality frameworks and data lineage tracking to ensure compliance with banking regulations and industry standards. Created real-time dashboards using Tableau and Amazon QuickSight, providing actionable insights for business decision-making. Enhanced data reliability by implementing robust data governance practices and securing pipelines with encryption and access controls.