Background: Companies House data only includes registered office addresses. We require the actual trading addresses (principal place(s) of business) for analysis, marketing outreach, or compliance.
Objective: Build a pipeline that takes a list of UK company numbers (and optional SIC codes), and outputs a CSV with:
Company number
Company name
Number of employees
Turnover (where available)
SIC code(s)
Trading address (street, city, postcode)
2. Scope of Work
Core Data Ingestion
Download/ingest the monthly Companies House bulk CSV (or use the Companies House API) to get company number, name, postcode, SIC code(s).
Trading-Address Enrichment
Primary method: Parse iXBRL filings for .
Fallback method: Query a Places‐API (e.g. Google Places or Foursquare) by “company name + postcode” to retrieve formatted address.
Data Merging & Cleanup
Consolidate registered vs. trading address fields.
Standardize address formatting.
Deduplicate and log failures for manual review.
Export & Delivery
Export a final CSV with the key fields.
Provide a short one-page README describing usage and dependencies
4. Required Skills & Experience
Strong Python (or Node.js) coding for data pipelines.
Experience parsing XBRL/iXBRL (e.g. python-iXBRL or equivalent).
Familiar with REST-API consumption (Companies House, Google/Foursquare, OpenCorporates).
Familiarity with web-scraping frameworks (Scrapy, BeautifulSoup, Puppeteer) is a plus.
Data cleansing and address standardization best practices.
Docker and CLI scripting for packaging (optional but preferred).
Milestones:
Core data ingestion + sample of 50 records
iXBRL enrichment + fallback API integration
Data cleanup, export & documentation
Please include in your proposal:
Relevant past projects / GitHub samples (especially XBRL or address-enrichment work).
Confirmation you can deliver the three key deliverables.
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