Data Engineer Intern - Web Crawling

The Data Engineer Intern at Sayari will focus on investigating and implementing web crawlers for new data sources, maintaining the existing crawling infrastructure, and improving metrics and reporting for web crawling. Additionally, the intern will help enhance and maintain ETL processes and contribute to the development and design of Sayari’s data products.

To excel as a Data Engineer Intern at Sayari, candidates should have experience with Python and managing web crawlers at scale, particularly frameworks like Scrapy. Familiarity with Kubernetes, Git collaboration, and working with selectors such as XPath and CSS is essential. Experience with web development tools and a proactive approach to bypassing anti-crawling techniques is also valuable.

Yes, the Data Engineer Intern role at Sayari is fully remote. Interns are expected to work between 20-30 hours per week, providing flexibility while contributing significantly to our exciting web crawling projects from anywhere.

While not mandatory, desirable skills for the Data Engineer Intern position at Sayari include experience with Apache projects like Spark and Airflow, familiarity with PostgreSQL or RocksDB, and exposure to cloud platforms like GCP, AWS, or Azure. Understanding API frameworks and knowledge graphs can also give candidates an edge.

The pay rate for the Data Engineer Intern position at Sayari ranges from $20 to $25 an hour, depending on the candidate's skills and experience. This competitive compensation reflects Sayari's commitment to valuing intern contributions while offering a meaningful learning experience.

When answering this question, describe specific projects where you’ve managed web crawling tasks, detailing the frameworks used, like Scrapy. Discuss challenges encountered, and how you optimized processes, which showcases your hands-on experience and problem-solving skills.

Discuss your approach to building robust crawling systems, including strategies for error handling, retries, and monitoring performance metrics. Highlight your understanding of load balancing and distributed systems, which reflects your technical depth in this field.

Share specific examples of Python projects you've worked on, particularly those relating to data processing or web scraping. Include libraries or frameworks used, such as Pandas or Requests, to demonstrate your programming proficiency and familiarity with the language's best practices.

Explain your experience using Git in team projects, focusing on version control practices, branching strategies, and handling merge conflicts. Demonstrating effective communication and collaboration skills through Git conveys your ability to work well in a team environment.

Talk about specific optimizations you've implemented in ETL processes, such as streamlining data flow, reducing processing times, or automating tasks. This shows your practical understanding of data engineering workflows and your ability to enhance data pipeline efficiency.

Present an engaging narrative about a specific challenge, detailing your thought process for troubleshooting. Focus on the outcome and what you learned, which will give insight into your problem-solving ability and resilience in challenging situations.

Outline your hands-on experience deploying applications using Kubernetes, discussing concepts like pods, services, and deployments. Your comfort level with container orchestration demonstrates your readiness to work in modern cloud environments.

Share your personal strategies for continuous learning, such as online courses or hands-on practice. Mention any recent technologies you’ve explored related to data engineering, showcasing your commitment to professional growth and adaptability.

Express your alignment with Sayari’s mission and commitment to innovative data solutions. Emphasize your eagerness to work in a collaborative environment and contribute to meaningful projects, which reflects your genuine interest in the company and its culture.

Describe your familiarity with PostgreSQL, including any projects where you utilized it for data storage or management. Discuss your understanding of database optimization and querying techniques, which can demonstrate your data handling expertise.