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I build modular Python data collection and ETL systems for public or authorized business data sources. I extract, normalize, validate, deduplicate, and enrich records from websites and APIs, then deliver reliable outputs to Google Sheets, CSV files, SQLite, or PostgreSQL. I completed a paid Upwork project covering five public data sources, a shared schema, multi-key deduplication, Google Sheets export, validation, tests, documentation, and source-code handoff. I can help with: • Python web scraping and multi-source data collection • Data extraction from websites and APIs, with CSV, Excel, or PDF processing when required • Data cleaning, normalization, validation, and deduplication • Google Sheets, CSV, Excel, SQLite, and PostgreSQL output • API data enrichment and scheduled ETL pipelines • Source tracking, error handling, tests, and documentation My typical workflow uses a separate adapter for each source, a shared normalized schema, deterministic validation rules, and quality checks before export. This keeps the pipeline maintainable and makes future sources easier to add. For new projects, I prefer starting with one representative source and a small paid milestone. We confirm access, required fields, output quality, and edge cases before expanding the full pipeline. Please include the target sources, required fields, sample output, update frequency, and preferred delivery format.

Anyone can scrape a page. The hard part — and what I do — is turning messy market data into something you can actually trade on: clean pipelines, point-in-time-correct databases, and bots that survive running 24/7. I build trading-adjacent data systems end to end: - Market data & pipelines — login-gated and JS-heavy sources, multi-source collection with failure isolation, normalized into Postgres/DuckDB - Point-in-time correctness — bitemporal databases with as-of replay and zero look-ahead leakage, so your backtests aren't lying to you - Signals & automation — rules-based market scanners, exchange API integration, Lightning/crypto automation, crash-resilient 24/7 deployment Recent work (real, with code & tests): - A bitemporal horse-racing trading database — Betfair historical pricing (600K+ price rows) + 280K+ race-card index, as-of replay validated leak-free, 176 passing tests (PostgreSQL/SQLAlchemy) - A Bitcoin (RoboSats) selling-automation system — 18-state order lifecycle, Lightning payments via Core Lightning, Tor routing, Docker API - A prediction-market arbitrage radar — scans 5,000+ live markets per cycle for YES/NO mispricing, DuckDB snapshots, 17 passing tests I care about correctness — bad data quietly ruins a trading system, so I build in reconciliation, idempotency and tests. Clear communication in English and Chinese. I'll tell you upfront if an edge isn't realistic rather than overpromising.

I am fluent in English and bilingual in Chinese and Cantonese, which allows me to work comfortably with international and cross-border projects. I value clear communication, reliable delivery, and attention to detail. I am a business-oriented data analyst with a strong foundation in accounting and economics, currently pursuing a Bachelor’s degree in Accounting in an English-taught program. I specialize in turning raw data into clear, actionable insights that support business decisions. I have hands-on experience with Excel, Python (pandas), data cleaning, data extraction, and basic ETL workflows, including working with APIs and structured datasets in academic projects and competitions. I focus on accuracy, clarity, and practical results rather than overly complex models. What I can help you with: Data cleaning, preprocessing, and organization Excel analysis, formulas, and structured reports Python (pandas) for data analysis and automation Data extraction from files or APIs Clear analytical summaries and presentations for business use If you are looking for a responsible entry-level data analyst who understands both numbers and business logic, I’d be happy to help.

Hi, I'm Bill, an experienced developer with a strong focus on backend developing, data engineering and automation. I am experienced in developing Restful API services, data scraping & cleaning & processing, FIX protocol, multi-source data integration, tool & script developing, etc. I mainly use Java & Python & C++ & SQL & shell, and am familiar with many technologies including MongoDB, MySQL, Redis, ClickHouse, ELK(Elasticsearch&Logstash&Kibana), Kafka, Zookeeper, Docker, K8s, MQ(ActiveMQ, RocketMQ, etc), Pandas, OpenPyXL, Numpy, FastAPI, Flask, etc.

I help e-commerce stores, businesses, and operators turn manual, time-consuming data tasks into fast, reliable, and error-free automated workflows. Whether you need to extract thousands of product listings from supplier websites, batch-download and rename image assets for auction/e-commerce catalogs, or sync messy data across platforms, I deliver clean, structured results. How I can help your business: • E-Commerce Data Extraction & Web Scraping: Extract product details, prices, specs, and variants from any protected or dynamic website using Python (Playwright/Scrapy/Selenium), Bright Data, or custom automated scrapers. • Catalog Preparation & Asset Processing: Format and map bulk inventory directly into target marketplace templates (eBay, LiveAuctioneers, Shopify, Zoro, Amazon). Automatically batch-download, organize, and rename thousands of high-res images to exact file-naming conventions in minutes. • Data Cleaning & Automated Formatting: Transform messy, inconsistent raw exports, PDFs, and spreadsheets into clean, structured CSV/Excel files with automated quality control checks to ensure zero missing fields or formatting errors. • Workflow Automation & API Integrations: Connect data across Google Sheets, Airtable, CRM systems, and e-commerce backends so your repetitive tasks run automatically. Why work with me: • Fast & Accurate Turnaround: Focused on 100% data integrity with no errors. • Simple Handoff: I deliver clean end-results (ready-to-use CSVs/organized assets) or lightweight automated scripts that you can easily run with one click. • Responsive & Clear Communication. Send over your target website, sample CSV/spreadsheet, or workflow description—let's make your data workflow fast and effortless.

🟩 Overview I help businesses turn complex, login-protected websites into clean, structured datasets ready for analysis. I specialize in extracting reliable data from dynamic websites, including pages with anti-bot protection and heavy JavaScript rendering. Recently completed projects: Healthcare data project: extracted 11,000+ records from a login-protected platform Investment dataset: structured 17,000+ Crunchbase records into clean CSV format I focus on delivering accurate, structured, and ready-to-use data — not raw or incomplete outputs. 🟨 What I deliver Clean, structured data (CSV / Excel / JSON) Reliable extraction from dynamic and protected websites Handling of login, pagination, and complex page structures Fast and consistent delivery (typically 24–48 hours depending on complexity) Scripts may be delivered depending on project requirements. 🟧 Tools & Technologies Python (Scrapy, Playwright, Requests, BeautifulSoup) Dynamic websites (JavaScript / React / Vue-based pages) Data extraction and cleaning workflows Automation for repetitive data collection tasks 🟦 Sample & Process I can provide a free sample (5–10 rows) within 12 hours after reviewing the target website, so you can evaluate the data quality before starting the full project. 🟩 Why me ✔ 100% Job Success Score ✔ Experience with complex and dynamic websites ✔ Structured, analysis-ready datasets (not raw scraping output) ✔ Fast and reliable communication ✔ Focus on accuracy and long-term usability 🟥 Next step Send me your website — I’ll quickly check feasibility and provide a sample before we start.