MySQL & Python Developer

1. SQL Development & Database Engineering

• Write and maintain SQL (MSSQL/MySQL) to develop and enhance feed content.
• Implement enhancements to the existing standard feed specification at the schema/query level.
• Administer the in-house database, including schema/data re-alignment.
• Build and maintain mapping logic for customised, client-specific feed variants.

2. Data Quality & Coverage QA

• Design and run QA queries against production databases to verify coverage at market, country, and asset-class level.
• Build repeatable coverage-reporting queries/scripts consumable by Sales, data support, and data quality teams.
• Investigate and resolve data gaps or inconsistencies identified through QA.

3. Feed Output & File Generation

• Generate report and file output (e.g. delimited/fixed-width feed files) directly from database content.
• Support trial content setup: extracting, mapping, and packaging subsets of data into new customised feeds.
• Assist in revisions to existing client feeds when new content is introduced via database.

4. Python-Based Data Extraction & Scraping

• Write Python scripts to extract structured data from external websites, APIs, and third-party sources to support feed content and coverage (e.g. requests/httpx, BeautifulSoup/lxml, Selenium/Playwright for JS-rendered pages).
• Build scraping/extraction jobs that handle pagination, rate limiting, and anti-bot measures (e.g. Cloudflare challenges), with appropriate retry and error-handling logic.
• Parse and normalise extracted data (HTML, JSON, XML, CSV) into structured formats suitable for loading into MSSQL/MySQL.
• Automate recurring data pulls and reconcile extracted data against existing database content to flag discrepancies or gaps.
• Maintain extraction/scraping scripts as source websites and APIs change, and document scraping logic alongside feed specifications.

5. Operational Troubleshooting

• Diagnose and resolve issues causing delay or failure of feed delivery.
• Support root-cause investigation across database, query, and file-generation layers.

6. Technical Documentation

• Maintain centralised, current technical documentation for feed specifications, schema structures, and mapping logic.
• Document all schema/database changes arising from database releases or client-specific amendments.
• Document data source URLs/endpoints, extraction logic, and known site-specific quirks for all Python scraping/extraction jobs.

7. Cross-Training & Knowledge Transfer

• Share database structure and query knowledge with other team members to build technical bench strength.