I ANALYZE.
I BUILD.
I AUTOMATE.
A Data & Technology professional working across Analytics, Data Engineering, Automation, and Application Development — turning complex business problems into dashboards, pipelines, and production systems.
WHAT I WORK WITH
Core technical domains aligned with real-world enterprise projects across Analytics, Data Engineering, App Platforms, and Automation.
Transforming raw enterprise data into executive dashboards, KPIs, and decision-support systems using Star Schema modeling, DAX time intelligence, and interactive visual reporting.
Building robust ETL pipelines, querying multi-table relational databases, cleansing large dataset footprints, and enforcing master data governance across enterprise storage layers.
Developing full-stack data applications, microservices APIs, and QR-based mobile tools that connect operational field teams directly to enterprise data repositories.
Automating repetitive spreadsheet tasks, building multi-platform web scraping bots, and leveraging OpenAI APIs to extract structured data from unstructured sources.
Staging and loading analytics data in cloud data warehouses, containerizing services, and managing cloud storage buckets for enterprise pipeline scalability.
Coordinating daily with cross-functional and international teams to align data standards, resolve issues, and present findings to stakeholders across regions.
BRIDGING DATA ENGINEERING & BUSINESS STRATEGY
I am a Data & Technology professional with a Master's in Computer Science (CGPA 8.4) and nearly 2 years of enterprise experience across heavy manufacturing (Innomotics India Ltd.) and multi-channel e-commerce (Sounce Retail).
I do more than create static reports — I work across the complete data lifecycle: extracting and engineering data from complex sources, building Star Schema models, automating manual operational bottlenecks with Python and VBA, and delivering decision-ready Power BI dashboards, full-stack software applications, and AI-assisted workflows.
WORKING METHODOLOGY
My dual-spectrum working methodology covering both Analytics Intelligence and Full-Stack Application/Data Platform Engineering.
ANALYTICS & BI METHODOLOGY
01 — Understand Business Needs
Understand stakeholders, requirements, KPIs and decision objectives before writing queries or code.
02 — Extract & Engineer Data
Query SQL databases, connect APIs, scrape web sources, and stage data through clean ETL pipelines.
03 — Clean, Model & Analyze
Wrangle data with Power Query/Pandas, build Star Schema models, write DAX, and run exploratory analysis.
04 — Automate Workflows
Automate manual reports using Excel VBA macros, Python automation scripts, and scheduled data refreshes.
05 — Visualize & Deliver
Develop interactive Power BI and Tableau dashboards with executive KPI cards and dynamic drill-downs.
06 — Validate & Improve
Validate data quality against ground-truth systems, refine business logic, and continuously iterate based on feedback.
APPLICATION & DATA PLATFORM METHODOLOGY
01 — Discover & Architect
Understand requirements, define scalable system architecture, data flow diagrams, and end-to-end solution design.
02 — Design the Data Layer
Design relational schemas (PostgreSQL / SQL Server), table relationships, indexing, and microservices API data contracts.
03 — Build the Application
Develop cross-platform client UIs (Flutter) and secure backend REST APIs (Spring Boot / Python) for business tools.
04 — Integrate & Secure
Connect APIs to databases and hardware scanners; implement JWT authentication, authorization, and secure data flows.
05 — Containerize, Test & Deploy
Containerize services with Docker, orchestrate on Kubernetes, execute ACP security validation, and deploy software.
06 — Maintain & Evolve
Monitor operational logs, troubleshoot issues, document APIs, and continuously improve production platforms.
PROFESSIONAL EXPERIENCE
DIGITAL PRODUCT & ANALYTICS SHOWCASES
Explore my portfolio of professional, project, and practice work. Hover over cards for live media previews or click any project to view its complete case study.
Education & Certifications
Formal Education
Master of Computer Science (MSc)
Advanced software engineering, database architectures, enterprise data modeling, machine learning fundamentals, and distributed system development.
Bachelor of Computer Science (BSc)
Computer science core foundations, object-oriented programming, data structures, algorithms, relational database design (SQL), and web technologies.