Chief Data Engineer
2 weeks ago
We are seeking a skilled Data Architect to lead the development of large-scale data pipelines, scraping systems, and integration with NoSQL stores.
This role is ideal for someone who thrives on early-stage challenges and loves building innovative, scalable solutions. As a key member of our engineering team, you will be responsible for designing and implementing high-performance data extraction tools, web crawlers, and data normalization processes.
You will be working closely with cross-functional teams to develop and implement robust data pipelines, ensuring seamless data flow and quality.
The ideal candidate will have strong proficiency in Python (libraries like BeautifulSoup, Scrapy, Selenium, Playwright, Requests) and experience in handling large-scale scraping with proxy management and rate-limiting.
Key Responsibilities- Data Scraping & Crawling: Develop automated scrapers to extract structured and unstructured data from websites, APIs, and public datasets.
- Scalable Scraping Systems: Design and implement multi-threaded, distributed crawlers capable of handling high-volume data collection without interruptions.
- Data Parsing & Cleaning: Normalize scraped data, remove noise, and ensure consistency before passing to data pipelines.
- Integration with Pipelines: Deliver clean, structured datasets into NoSQL stores and ETL pipelines for further enrichment and graph-based storage.
- At least 2 years of experience in web scraping, crawling, or data collection.
- Strong proficiency in Python (libraries like BeautifulSoup, Scrapy, Selenium, Playwright, Requests).
- Familiarity with NoSQL databases (MongoDB, DynamoDB) and data serialization formats (JSON, CSV, Parquet).
- Experience in handling large-scale scraping with proxy management and rate-limiting.
- Basic knowledge of ETL processes and integration with data pipelines.
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