Nitai Baboolal
Integration Specialist, Cloud FinOps Analyst, Analytics Engineer
Enterprise integration, multi-cloud FinOps and analytics engineering across AWS, GCP and Azure, plus quantitative research and security tooling.
Tools & platforms I work with
- AWS
- Google Cloud
- Azure
- Python
- SQL
- BigQuery
- Athena
- Power BI
Capabilities
Data & Quant
Machine learning, analytics engineering and quantitative research — cost-forecasting models, ETL pipelines and back-tested trading strategies.
Integration
Enterprise integration at Standard Bank: event management and monitoring, plus architecture documentation for IBM DataPower, ACE/IIB and MQ.
Architecture documentation
Dashboard check
As-is review
Cloud & FinOps
Multi-cloud cost visibility, forecasting and optimisation across AWS, GCP and Azure — from Cost Explorer and BigQuery reporting to Lambda-driven anomaly detection.
Find me online
Site, code and verified badges.
Analytics
End-to-end analytics: reporting what happened, diagnosing why, forecasting what's next and recommending what to do.
Projects
At a glance
Core areas
Clouds & platforms
- AWS
- Google Cloud
- Azure
- IBM DataPower
- IBM MQ
About
I'm an Integration Specialist at Standard Bank Group, focused on integration architecture and event management, and a Cloud FinOps Analyst and Analytics Engineer across AWS, GCP and Azure.
The through-line is making complex systems reliable and their costs and data legible: enterprise integration, multi-cloud cost optimisation and data science, alongside quantitative research at NPro Technology and security tooling.
What I enjoy most is turning complex data findings into actionable recommendations with multidisciplinary teams.
Experience
- Decommission Nagios host systems.
- Document IBM integration architecture: DataPower, with as-is reviews of ACE/IIB and MQ.
- Manage events by monitoring dashboards and system environments, keeping key applications proactively available to customers.
- Diagnose, resolve, document and escalate system incidents through to resolution.
- Communicate system issues that affect the quality or reliability of supported systems to clients, peers and management.
- Run daily, weekly, monthly and year-on-year trend analysis to identify hot spots.
- Architected, engineered and secured a Slack AI agent that answers AWS cost queries using Amazon Q Developer, Claude and the AWS Pricing API.
- Implemented machine learning models that forecast business-unit costs, accounting for seasonality, trend and noise.
- Engineered an AWS Lambda solution for cost anomaly detection that queries AWS Cost Explorer, is triggered by EventBridge and sends alerts via SES.
- Developed and deployed automated AWS Lambda FinOps tools that detect idle instances, helping reduce unnecessary compute costs.
- Automated early-warning cost detection in BigQuery, enabling proactive financial interventions and improved budget oversight.
- Ran ad-hoc SQL queries in AWS Athena to surface actionable insights into team-level cloud spending patterns.
- Managed the monthly GCP cloud financial reporting process in BigQuery.
- Monitored daily cloud spend and produced weekly and monthly reports, including weekly cost tracking for the Head of Engineering (Shoprite Technology).
- Built AWS Cost Explorer reports to cut the time taken for Data and Analytics cost reporting.
- Analysed cloud usage data to prioritise and recommend optimisation strategies, identifying significant potential savings.
- Advised Engineering teams on cost optimisation strategies such as rightsizing and power scheduling, and worked with them to implement best practices and recommendations.
- Prepared detailed quotations for AWS system changes, supporting informed decision-making and effective budget management.
- Cross-account Terraform migration: led the migration of Terraform-managed AWS resources from one AWS account to another.
- Pipeline and configuration cutover: refactored Airflow DAGs and AWS Glue jobs for the target account.
- Discover alpha opportunities in commodities and foreign exchange markets.
- Design trading strategies around defined risk management profiles.
- Develop and backtest predictive models.
- Developed and maintained automated Power BI dashboards giving enterprise clients visibility of AWS and Azure costs.
- Built weekly and monthly FinOps reports highlighting anomalies, top spend areas, savings opportunities and purchase plan coverage.
- Presented insights in bi-weekly client review sessions, aligning on cloud spend trends and recommending optimisation actions.
- Wrote SQL queries to identify idle, unattached and over-provisioned resources, and supported AI model testing for anomaly detection pilots.
- Helped implement a savings tracker that monitors realised and projected savings across multiple accounts.
- Investigated high-cost services such as data transfer, backup storage and orphaned resources in depth.
- Provided guidance on cloud cost management best practices, including rightsizing, scheduling and reserved instance coverage.
- Analysed large datasets to identify patterns, trends and emerging behaviours.
- Applied advanced statistical methods, including t-tests and ANOVA to compare groups and correlation coefficients to find relationships in the data.
- Gathered data from multiple sources and compiled it into automated SPSS dashboards.
- Collaborated with department members and internal customers on ongoing decisions about data collection, analysis and methodology.
Education
Data science on top of an ICT degree, with an engineering start.
Certifications
10 certifications from AWS, IBM, Microsoft and UC San Diego.
- AWS
AWS Certified Machine Learning Specialty
View on Credly - IBM
IBM Advanced Deep Learning Specialist
View on Credly - AWS
AWS Certified Cloud Practitioner
View on Credly - IBM
IBM Deep Learning with PyTorch
View on Credly - IBM
IBM Deep Learning with Keras and TensorFlow
View on Credly - IBM
IBM Introduction to Deep Learning and Neural Networks with Keras
View on Credly - Microsoft
Microsoft Certified: Azure Fundamentals
View on Credly - Microsoft
Microsoft Certified: Security, Compliance, and Identity Fundamentals
View on Credly - IBM
IBM DevOps, Cloud, and Agile Foundations
View on Credly - UC San Diego
Algorithmic Toolbox (UC San Diego)
View on Credly