Experienced in data pipelines and data-intensive software development. I built GovernmentNinja, OutMatch, PollBuzz and BulkFlow and continue to build more. heresuryanshsingh@gmail.com
GovernmentNinja — live
Government job discovery, eligibility checking and job alerts. A platform where you never miss an opportunity in the government sector.
- 100,000+ impressions, 3,000+ clicks and 100+ signed-up users in the first two months of deployment
- 1,900+ postings aggregated, listed and quality-tested automatically
- A 20+ step automated pipeline: source aggregation → cleaning → transformation → validation → testing → target load → email reminders → job alerts, on a schedule
- 95%+ on SEO, performance and accessibility in PageSpeed Insights — achieved while running inside Cloudflare Workers' 10 ms CPU free-tier limit, which forced optimisation at every layer
- Account management across five roles: user, contributor, publisher, admin, superadmin
- Custom prompt engineering for token-optimised highlight generation during pipeline runs
- Analytics, monitoring and GitHub Actions workflows throughout
Source kept private to prevent plagiarism — access available on request.
OutMatch — live
Visibility is won, never bought. A global leaderboard where a brand survives the ranking only if people vote for it. Submit a brand, product or idea; a chess Elo rating ranks it on head-to-head match performance.
Source kept private to prevent plagiarism — access available on request.
Real-time polling platform where users run a poll campaign for a fixed window and results update live. React + Hono on a single Cloudflare Worker, D1 for storage, Durable Object WebSocket fan-out with serialised vote counting.
Large-dataset upload and processing — 85,000+ row spreadsheets with no data loss. Cloudflare Workers, Queues and R2 for streamed objects, D1 for records, and live per-row progress over a hibernating Durable Object.
Menus Processing Microservice — Go pipeline · Spring Boot service
A dedicated parallel processing pipeline turning a food-menu dataset into cleaned JSON: Google Cloud Storage extraction, parsing, transformation and target allocation.
| Cloud & Big Data | Azure Data Factory, ADLS Gen2, Azure Databricks, Microsoft Fabric, PySpark |
| Data Engineering | ETL/ELT pipelines, data cleaning, validation, warehousing, modeling, Medallion (Bronze/Silver/Gold) architecture |
| Databases | PostgreSQL, MongoDB, SQL querying, Drizzle ORM |
| Languages | Python, SQL, JavaScript, TypeScript, C++ |
| Libraries | NumPy, Pandas, pytest, React, Next.js, Node.js, Express |
| Tools | Git, GitHub, GitHub Actions, Cloudflare Workers, JIRA, Notion |
Data Engineer Intern — Crowe · Feb 2026 – Jul 2026 Built and maintained Azure ELT pipelines with ADF, ADLS Gen2 and Databricks for client datasets, covering transformation, validation and downstream reporting. Wrote data-quality automation for the Data Analytics testing function, and developed MCP architecture for the department's AI configuration.
Full Stack Developer — ShelfEx · Jul 2025 – Jan 2026 Led backend development of a new product from scratch to production, designing the data models and APIs. Worked directly with the client (PepsiCo) to gather requirements and fold in feedback across the development lifecycle.
Teaching Assistant — Internshala · Jan 2025 – Feb 2025 Reviewed and evaluated student full-stack codebases and ran daily doubt-clearing sessions.
B.Tech, Computer Science & Engineering — 2022–2026 · CGPA 8.07/10