Nitai Baboolal
AI/ML || Data Analytics
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About
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.
Experience
Analytics Engineer
April 2025 - Present
ShopriteX
- 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 The Shoprite Group of Companies
- 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
NPro Technology
- 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
OneNebula
- 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 – June 2022
- Conducted analysis on large data sets to identify patterns, trends, emerging behaviors, etc.
- Applied advanced statistical data analysis methods.
- 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).
Isifundiswa Electrical Contractors – Electrician (Weekends Part-time)
January 2016 – December 2018
- Distribution boards (Single and Three phase)
- Earthing o Insulation resistance o Transformer maintenance o Surge protection
- Fault finding and rectifying incorrect wiring
Education
PGDip (Eng) Industrial Engineering (Data Science)
2024 - 2025
Stellenbosch University
- Applied Machine Learning
- Optimisation
- Big Data
- Data Analytics
2022
Durban University of Technology
- 18 Distinctions
- 77% & 75% average in second and third year
- BankSeta bursary