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10a Labs

Data Engineer, Web Scraping

Washington D.C.$105k–$125kmidAdded 1 month ago

About this role

10a Labs seeks a Data Engineer specializing in web scraping to build robust data pipelines for AI safety and threat intelligence. You'll design end-to-end data collection systems, process both structured and unstructured data, and collaborate across teams to deliver insights and tools in a fast-paced, security-focused environment.

What you'll do

  • Design and optimize data pipelines for web scraping and data processing on cloud platforms
  • Perform ad hoc web scraping and data collection to support research initiatives
  • Clean, transform, and anonymize data for downstream analysis
  • Develop internal and external APIs following best practices
  • Collaborate with ML engineers and software developers on dashboards, APIs, and data deliverables
  • Support critical initiatives in AI safety and threat intelligence

What they're looking for

  • Python and SQL programming
  • Web scraping tools (Beautiful Soup, Selenium, Scrapy)
  • Google Cloud Platform (or equivalent cloud services)
  • Data pipeline design and orchestration (Airflow, Cloud Composer)
  • Database management (CloudSQL, Cloud Spanner)
  • Text data processing and transformation
  • Technical communication to non-technical audiences
  • API development

Benefits

  • Salary: $105K–$125K based on experience
  • Performance-based annual bonus
  • Comprehensive health, dental, and vision coverage
  • Generous PTO and paid holidays
  • Professional development support for conferences and training
  • Fully remote, U.S.-based position with 401(k) plan
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10a Labs

10a Labs builds AI safety and threat intelligence solutions that help organizations detect and mitigate risks in AI systems. The company is hiring backend engineers, machine learning engineers, and data engineers to develop scalable APIs, ML systems, and data pipelines that power these safety-focused applications.

View all jobs at 10a Labs

Likely interview questions

  • Walk us through a web scraping project you've built end-to-end. What tools did you use, and how did you handle scale or rate limiting?
  • Describe your experience with Google Cloud Platform. Which services have you used for data pipelines, and how did you choose between options like Cloud Composer, Cloud Run, and Pub/Sub?
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