Senior Data Collection Engineer (Python / Web Scraping)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 64d ago
The date the source published, not the day we noticed it (2026-07-13). Last seen at its source just now.
Is it remote?
The listing says yes
The location field doesn't say remote, so our assessment is based on the title or the description. Read the listing before applying.
Who may apply?
Brazil, Mexico, Argentina, Uruguay, Colombia
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $95.9k–157.1k/yr
Middle 50% of 8 listings that do state pay — Engineering · Senior · Brazil · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
ashby employer's own board first seen 11d ago · last seen just now
The listing
Our client is a fast-growing, remote-first B2B SaaS company where large-scale data collection is at the core of the product. As the platform continues to grow globally, they're looking for an experienced Data Collection Engineer to help build and scale the infrastructure behind one of their core product capabilities.
This is a hands-on engineering role focused on designing resilient scraping infrastructure, overcoming sophisticated anti-bot systems, and collecting high-quality data at scale. You'll own the entire lifecycle of large-scale data collection pipelines, ensuring they remain reliable, scalable, and resilient as the product continues to grow.
Responsibilities
Infrastructure Strategy & Architecture: Architect, build, and maintain the core infrastructure behind our large-scale asynchronous data collection platform.
Advanced Resilience Engineering: Design, implement, and continuously improve sophisticated anti-blocking strategies, including browser fingerprinting, proxy rotation, CAPTCHA handling, and other techniques required to maintain reliable data collection.
Core Development: Design, develop, test, and maintain robust scraping components using Python and modern scraping frameworks such as Playwright, Scrapy, Selenium, Requests, and related tools.
Operational Excellence: Build monitoring, alerting, and logging systems that help identify issues quickly and continuously improve scraper reliability and data quality.
Data Pipelines & Integrations: Develop and maintain scalable data ingestion pipelines and integrations with internal and external REST APIs.
DevOps & Automation: Contribute to infrastructure automation using Docker, CI/CD pipelines, Linux environments, and related DevOps practices.
Collaboration: Work closely with other engineers to improve our scraping platform, establish engineering standards, and mentor less experienced teammates.
RequirementsStrong commercial experience building high-volume web scraping and data collection systems using Python.
Deep practical knowledge of anti-bot techniques, including browser fingerprinting, CAPTCHA solving, proxy management, and blocking mitigation.
Strong understanding of asynchronous programming, browser automation, HTML parsing, HTTP protocols, and REST APIs.
Hands-on experience with Playwright, Scrapy, Selenium, or similar scraping frameworks.
Experience working with Docker, Linux, Git, and modern software development practices.
Familiarity with SQL and NoSQL databases.
Strong ownership mindset with the ability to independently drive complex technical projects.
Fluent English communication skills.
Nice to Have
Experience with advanced asynchronous frameworks (asyncio, Celery, distributed task queues).
Experience building monitoring and data quality validation systems.
Experience mentoring engineers or helping technical teams scale.
Experience using modern AI-assisted development tools (Claude Code, Cursor, Codex, Windsurf, or similar).
We value engineers who use AI as an engineering multiplier—guiding, reviewing and orchestrating AI-generated solutions rather than writing every implementation detail manually.
What We OfferHigh ownership and the opportunity to make a measurable impact on a rapidly growing product.
Remote-first culture with flexible working arrangements.
Competitive compensation package.
Personal and professional development through ongoing learning and coaching.
A collaborative international engineering team solving technically challenging problems.
Optional office near Berlin at the Wildau Tech University campus.