Nitai Baboolal

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.

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.

Cloud Financial Operations Analyst

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.

Chief Quantitative researcher, engineer & founder

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.

Junior Financial Operations Analyst

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.

Brainnest - Data Analyst Work Experience Program (Remote part-time)
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

PGDip (Eng) Industrial Engineering (Data Science)

2024 - 2025

Stellenbosch University

• Applied Machine Learning
• Optimisation
• Big Data
• Data Analytics

Bachelor of Information and Communications Technology

2022

Durban University of Technology

• 18 Distinctions
• 77% & 75% average in second and third year
• BankSeta bursary