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In this role you will help optimize data collection as a Python Developer in our scraping team. You will design, implement, and document robust Scrapy spiders to withstand website changes while preserving existing functionality. You’ll ensure high data quality through code reviews and validation, and build sophisticated crawlers that navigate anti-bot measures. You will contribute to major developments across codebases and share knowledge through documentation and training. This is a chance to shape scalable data pipelines for real-time market visibility in a fast-growing, startup-minded environment.
Compensaciones / Ventajas
Flexible working environment
Volunteer time off
LinkedIn Learning
Employee-Assistance-Program (EAP)
Responsabilidades
Design, implement and document Scrapy spiders for robust data collection
Perform code reviews and data validation to ensure quality
Develop crawlers that handle anti-bot measures using HTTP and browser techniques
Architect and contribute to new developments across multiple codebases with documentation and training
Collaborate with cross-functional teams to share knowledge and enable tooling improvements
Requisitos principales
Master in Computer Science, IT, or related field
At least 3 years of professional software engineering experience
Knowledge of BeautifulSoup or Scrapy
Familiarity with HTML and JavaScript, understanding of SPAs
Experience with xkdbapo RESTful and/or GraphQL APIs
Hands-on experience with Django, FastAPI or similar Python frameworks
Scrapy knowledge is a plus
Experience with time series databases like InfluxDB is advantageous
Strong skills in Docker, Git, pandas, regex, Linux, and bash scripting
Proven experience with AWS, GCP, or Azure
Enthusiastic and motivated
Autonomous and proactive
Enjoys tackling challenging software engineering problems
Scrapy
BeautifulSoup
HTML/JavaScript
📌 Web Scraper (Barcelona)
🏢 Jobrapido
📍 Barcelona
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Muestra tus habilidades a la empresa, rellenar el formulario y deja un toque personal en la carta, ayudará el reclutador en la elección del candidato.