Do data engineers do web scraping?

Feb 5, 2024 ยท 2 min read

Web scraping, also known as web data extraction, is the process of collecting structured web data in an automated fashion. As data volumes continue growing exponentially, web scraping has become an essential skill for data engineers.

Data engineers build and maintain data pipelines that acquire data from various sources, transform and cleanse it, and load it into databases and data warehouses. While many pipelines connect to internal databases or REST APIs, the open web contains a treasure trove of valuable data. Web scraping enables data engineers to efficiently collect this data.

Why Web Scraping is Useful for Data Engineers

Here are some examples of why web scraping is an important data engineering skill:

  • Competitive pricing data: Scrape competitor prices daily to dynamically adjust your own pricing
  • Sentiment analysis: Extract social media posts to gauge brand sentiment over time
  • Lead generation: Build a database of prospects by scraping industry directories
  • Research: Gather data for analysis that isn't available via API or datasets
  • Web scraping helps data engineers acquire external data sources, enrich existing analytics, and identify new business opportunities.

    Web Scraping Challenges

    However, web scraping brings unique development and maintenance challenges:

  • Fragile scrapers: Sites change often, breaking scrapers. Scrapers need ongoing monitoring and tweaking.
  • Data integrity: Scraped data can have quality issues needing cleansing.
  • Ethical concerns: Respect site terms of service and data privacy regulations.
  • Web Scraping Best Practices

    Here are some tips for reliable, scalable web scraping:

  • Use robust libraries like Python Scrapy and node.js puppeteer instead of brittle regex parsing
  • Containerize scrapers for smooth deployment into production pipelines
  • Monitor scrapers and validate sampled data continuously
  • Throttle requests and insert random delays to avoid overloading sites
  • Follow robots.txt directives and check terms of service
  • Anonymize personal data and allow opt-outs
  • With the right precautions, web scraping can supply data engineers with fertile, up-to-date data to drive impactful analytics. While challenging, web data extraction is an invaluable skill for unlocking unique datasets.

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