
Over four months, contributed to the alltheplaces/alltheplaces and osmlab/name-suggestion-index repositories by building and refining data ingestion pipelines, web scrapers, and data hygiene processes. Developed Scrapy spiders in Python to extract, validate, and categorize location data from diverse APIs, expanding coverage for hospitals, banks, parking facilities, and petrol stations. Addressed data quality by implementing coordinate validation, standardizing brand mappings, and cleaning deprecated entries, ensuring reliable downstream analytics and mapping. Leveraged skills in data extraction, mapping, and validation, while maintaining JSON and JavaScript data structures. The work emphasized robust data modeling, brand consistency, and maintainable categorization across evolving datasets.
March 2025 monthly summary focused on delivering data quality improvements, branding consistency, and reliable categorization across two repositories. Highlights include standardizing categorization for bicycle rentals in the GBFS spider, cleaning and refining financial data in the name-suggestion-index, and unifying brand naming from Total/Total Access to TotalEnergies.
March 2025 monthly summary focused on delivering data quality improvements, branding consistency, and reliable categorization across two repositories. Highlights include standardizing categorization for bicycle rentals in the GBFS spider, cleaning and refining financial data in the name-suggestion-index, and unifying brand naming from Total/Total Access to TotalEnergies.
February 2025 focused on data expansion, brand accuracy, and data hygiene across two repositories. Key outcomes include expanding data coverage with Brazil petrol stations, introducing SIM as a new category, integrating Total Energies and removing the Total Access feature, and conducting comprehensive cleanup of deprecated names and banks. These efforts improved data completeness, search relevance, provider matching, and maintainability, delivering clear business value for downstream analytics and user-facing features.
February 2025 focused on data expansion, brand accuracy, and data hygiene across two repositories. Key outcomes include expanding data coverage with Brazil petrol stations, introducing SIM as a new category, integrating Total Energies and removing the Total Access feature, and conducting comprehensive cleanup of deprecated names and banks. These efforts improved data completeness, search relevance, provider matching, and maintainability, delivering clear business value for downstream analytics and user-facing features.
January 2025 performance highlights: expanded data coverage and quality across two core repositories by delivering three new features and performing targeted data hygiene updates. The work strengthened data accuracy for location-based search, improved brand integrity, and demonstrated end-to-end data engineering from scraping and API ingestion to cleanup and mapping updates.
January 2025 performance highlights: expanded data coverage and quality across two core repositories by delivering three new features and performing targeted data hygiene updates. The work strengthened data accuracy for location-based search, improved brand integrity, and demonstrated end-to-end data engineering from scraping and API ingestion to cleanup and mapping updates.
December 2024: Delivered data reliability improvements and expanded coverage across two new data sources. Key outcomes include a robust coordinate validation fix preventing address/country mismatches from corrupting Skoda scraping data; two new data-spider features expanding geographic coverage: HealthHub SG (32 hospitals) and Pase.com.mx (parking lots). The work enhances data quality, reduces downstream errors, and enables better analytics and mapping. Technologies demonstrated include Scrapy, dynamic API key handling, reverse_geocoder-based country validation, and robust data modeling (IDs, names, addresses, coordinates).
December 2024: Delivered data reliability improvements and expanded coverage across two new data sources. Key outcomes include a robust coordinate validation fix preventing address/country mismatches from corrupting Skoda scraping data; two new data-spider features expanding geographic coverage: HealthHub SG (32 hospitals) and Pase.com.mx (parking lots). The work enhances data quality, reduces downstream errors, and enables better analytics and mapping. Technologies demonstrated include Scrapy, dynamic API key handling, reverse_geocoder-based country validation, and robust data modeling (IDs, names, addresses, coordinates).

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