AMITESH
SINGH
I engineer scalable data pipelines and robust backend systems that turn raw, complex information into strategic business decisions.
My expertise bridges traditional software engineering and modern analytics. From designing deterministic C++ risk-scoring engines to automating massive ETL workflows on Google Cloud Platform, I focus on building systems that prioritize data integrity, security, and high performance.
I believe in practical, scalable solutions over unnecessary complexity. Whether it is consolidating multi-source financial data or designing executive Looker Studio dashboards, my goal is to deliver clean logic, reliable architecture, and actionable insights that stakeholders can trust.
- SQL
- Python
- C++
- Google BigQuery (GCP)
- MySQL
- PostgreSQL
- Power BI
- Looker Studio
- Microsoft Excel
- Docker
- ETL Pipelines
- Git
- GitHub
- Campaign Analytics
- Performance Reporting
- Customer Segmentation
- Technical Documentation
Engineered a high-performance C++ fraud detection engine implementing deterministic risk-scoring (0-100) to evaluate transaction frequency, volume spikes, and geo-location anomalies. Enforced regulatory compliance by building a 24-hour rolling limit system (Rs. 1,00,000) with dual-entry audit logging, automatically isolating accounts at ≥70 risk to prevent asset loss.
Architected a containerized ETL pipeline using Python and Docker to extract, transform, and load 540K+ transactional records onto Google Cloud Platform. Leveraged BigQuery for complex RFM segmentation, achieving a robust 96% reduction in data processing time compared to manual workflows while delivering actionable data-driven insights.
Designed an end-to-end analytics workflow processing 95,000+ e-commerce transactions, utilizing complex SQL multi-table joins to ensure 100% data integrity for audit-ready reporting. Developed dynamic Looker Studio dashboards specifically tailored for business stakeholders to visualize key performance indicators and seasonal sales trends.
- Designed a data-backed bidding strategy framework using SQL and Excel, analyzing over 5,000 rows of historical project data to identify and prioritize key profit drivers.
- Consolidated multi-source budget variance data across 50+ projects, eliminating ~3 hours of manual reporting per week and significantly improving accuracy for the finance team.
- Developed dynamic Power BI dashboards to monitor 10+ active projects, enabling project manager to proactively track budgets and detect early cost-overruns.
Built a rigorous technical foundation in software engineering, algorithmic problem solving, and data architecture. Applied core computer science principles to engineer scalable backend systems and optimize data pipelines.
CGPA: 8.6
Developed a foundational digital toolkit and mastered the McKinsey approach to structured problem-solving, effective business communication, and adaptable mindsets for the future of work.
Applied SQL, data cleaning protocols, and end-to-end analytics workflows to derive insights from real-world datasets, demonstrating proficiency in data-driven decision-making and storytelling with data.
Completed a simulated project involving data analysis and strategic decision-making to solve complex business challenges for clients, demonstrating practical application of analytics skills in a consulting context.
Let's worktogether
If you're looking for someone who can work with data and deliver clear, reliable insights — let's connect.