Nitai Baboolal
Cloud FinOps Analyst | Analytics Engineer
Apps
A collection of interactive applications I've built.
About Me
Driven by a passion for optimizing cloud costs and delivering strategic insights, I am a seasoned Cloud FinOps Analyst with an Analytics Engineering secondment and a Postgraduate Diploma in Industrial Engineering (Data Science) from Stellenbosch University. Throughout my career, I have harnessed advanced analytics, machine learning, and cloud computing to architect and implement cost-effective solutions across AWS, GCP, and Azure environments. At The Shoprite Group, I developed and deployed predictive cost-forecasting models and automated anomaly-detection pipelines using AWS Lambda, Cost Explorer, EventBridge, and SES, resulting in a proactive FinOps framework that improved budget oversight and delivered measurable savings. My tenure at ShopriteX involved leading cross-account Terraform migrations and refactoring Airflow DAGs and AWS Glue jobs, ensuring seamless infrastructure transitions. I complement my practical experience with robust quantitative research skills as the Chief Quantitative Researcher at NPro Technology, where I design and back-test trading strategies in commodities and foreign-exchange markets. My technical toolkit includes Python, SQL, BigQuery, Athena, PowerBI, and industry-standard machine-learning libraries. Adept at translating complex data findings into actionable business recommendations, I excel in collaborating with multidisciplinary teams to drive operational excellence, enhance financial performance, and align technology solutions with organizational goals. I hold 15 industry certifications.
Skills & Abilities
A showcase of my technical and professional capabilities.
Professional Experience
April 2025 - Present
- Cross-Account Terraform Migration: Spearheaded the migration of Terraform-managed AWS resources from one account to another.
- Pipeline & Configuration Cutover: Refactored Airflow DAGs and AWS Glue jobs for the target account.
March 2024 - Present
- Implemented Machine Learning Models to forecast business unit costs.
- Engineered AWS Lambda solution to query AWS Cost Explorer for cost anomaly detection triggered by Event Bridge and sent using SES.
- Developed and deployed custom FinOps automation tools using AWS Lambda for idle instance detection, helping reduce unnecessary compute costs.
- Leveraged BigQuery to automate early-warning cost detection, enabling proactive financial interventions and improved budget oversight.
- Executed ad-hoc SQL queries via AWS Athena/Big Query to extract actionable insights into team-specific cloud spending patterns.
- Built AWS Cost Explorer reports to reduce time taken for Data and Analytics cost reporting.
- Monitored daily cloud expenditures and prepared comprehensive weekly and monthly reports for senior management review.
- Analysed cloud usage data to collate, prioritize, and recommend optimization strategies, identifying significant potential savings.
- Provided expert guidance on cloud cost optimization strategies—including rightsizing and power scheduling—to drive cost reduction initiatives.
- Collaborated closely with Engineering teams to implement best practices and actionable cost optimization recommendations.
- Prepared detailed quotations for AWS system modifications, supporting informed decision-making and effective budget management.
September 2024 - Present
- Discovering Alpha opportunities within Commodities and Foreign Exchange markets.
- Creating trading strategies based on Risk Management profiles.
- Development and Back Testing of predictive models.
January 2023 – Feb 2024
- Analysed cloud expense data across both AWS and Azure environments to uncover actionable cost-saving opportunities.
- Developed intuitive PowerBI dashboards tailored to client specifications for enhanced visibility into cloud spending.
- Delivered clear, data-driven presentations of key findings and cost optimization strategies to clients.
- Utilized SQL and Python scripts to find abnormalities within the data.
- Provided strategic rightsizing recommendations to optimize resource allocation and reduce unnecessary cloud spending.
March 2022 – April 2022
- Conducted analysis on large data sets to identify patterns, trends, emerging behaviors, etc.
- Applied advanced statistical data analysis methods.
- Collaborated with members of the department and internal customers in ongoing decisions regarding data collections, data analysis and methodology.
- Gathered data from multiple sources and cohesively compile and create automated dashboards using SPSS.
- Compared results from one group of people with results from one or more other groups (t-test and ANOVA).
- Calculating correlation coefficient for finding relationships in the data.
Education
2024 - 2025
- Applied Machine Learning
- Optimisation
- Big Data
- Data Analytics
2022
- 18 Distinctions
- 77% & 75% average in second and third year
- BankSeta bursary
Certifications & Accolades
Proof of my commitment to continuous learning and professional development.
AWS Certified Machine Learning Specialty
IBM Advanced Deep Learning Specialist
AWS Certified Cloud Practitioner
IBM Deep Learning with PyTorch
IBM Deep Learning with Keras and Tensorflow
IBM Introduction to Deep Learning and Neural Networks with Keras
Microsoft Certified Azure Fundamentals
Microsoft Certified: Security Compliance and Identity Fundamentals
IBM DevOps, Cloud, and Agile Foundations
University of California: San Diego Algorithmic Toolbox
Featured Projects
A selection of projects that demonstrate my skills and experience.
Get In Touch
I'm always open to discussing new projects, creative ideas, or opportunities.
Feel free to reach out through any of the channels above. I look forward to hearing from you!