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About the role
As a Senior Data Engineer at our company, you will be responsible for designing and implementing scalable web scraping systems capable of handling high-volume, high-velocity data sources. You will develop responsive and semantic scraping solutions using advanced AI and NLP methods to extract meaningful, context-rich information. Additionally, you will architect and build data pipelines from scratch, integrating structured and unstructured data across multiple platforms. Your role will also involve establishing reliable, fault-tolerant data architectures for long-term scalability and maintainability, as well as integrating scraped data into RAG (Retrieval-Augmented Generation) and other intelligent workflows. You will continuously enhance scraping performance, pipeline efficiency, and data quality through automation and innovation. Key Responsibilities: - Design and implement scalable web scraping systems capable of handling high-volume, high-velocity data sources. - Develop responsive and semantic scraping solutions using advanced AI and NLP methods to extract meaningful, context-rich information. - Architect and build data pipelines from scratch, integrating structured and unstructured data across multiple platforms. - Establish reliable, fault-tolerant data architectures for long-term scalability and maintainability. - Integrate scraped data into RAG (Retrieval-Augmented Generation) and other intelligent workflows. - Continuously enhance scraping performance, pipeline efficiency, and data quality through automation and innovation. Required Skills and Qualifications: - 5+ years of experience in data engineering, data scraping, and pipeline development. - Proven track record of building end-to-end data systems from the ground up. - Deep knowledge of web scraping tools (Scrapy, Selenium, BeautifulSoup) and anti-blocking, concurrent scraping strategies. - Strong understanding of AI-driven data extraction, NLP, and semantic enrichment. - Experience implementing RAG pipelines and integrating LLMs with retrieval systems. - Familiarity with cloud infrastructure (AWS/GCP/Azure) and CI/CD best practices. If you're passionate about turning large-scale web data into meaningful, AI-ready insights, we welcome you to join our team. As a Senior Data Engineer at our company, you will be responsible for designing and implementing scalable web scraping systems capable of handling high-volume, high-velocity data sources. You will develop responsive and semantic scraping solutions using advanced AI and NLP methods to extract meaningful, context-rich information. Additionally, you will architect and build data pipelines from scratch, integrating structured and unstructured data across multiple platforms. Your role will also involve establishing reliable, fault-tolerant data architectures for long-term scalability and maintainability, as well as integrating scraped data into RAG (Retrieval-Augmented Generation) and other intelligent workflows. You will continuously enhance scraping performance, pipeline efficiency, and data quality through automation and innovation. Key Responsibilities: - Design and implement scalable web scraping systems capable of handling high-volume, high-velocity data sources. - Develop responsive and semantic scraping solutions using advanced AI and NLP methods to extract meaningful, context-rich information. - Architect and build data pipelines from scratch, integrating structured and unstructured data across multiple platforms. - Establish reliable, fault-tolerant data architectures for long-term scalability and maintainability. - Integrate scraped data into RAG (Retrieval-Augmented Generation) and other intelligent workflows. - Continuously enhance scraping performance, pipeline efficiency, and data quality through automation and innovation. Required Skills and Qualifications: - 5+ years of experience in data engineering, data scraping, and pipeline development. - Proven track record of building end-to-end data systems from the ground up. - Deep knowledge of web scraping tools (Scrapy, Selenium, BeautifulSoup) and anti-blocking, concurrent scraping strategies. - Strong understanding of AI-driven data extraction, NLP, and semantic enrichment. - Experience implementing RAG pipelines and integrating LLMs with retrieval systems. - Familiarity with cloud infrastructure (AWS/GCP/Azure) and CI/CD best practices. If you're passionate about turning large-scale web data into meaningful, AI-ready insights, we welcome you to join our team.