This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer - Web Scraping based in Turkey.

This role is an exciting opportunity to build scalable web scraping solutions and data pipelines that power business-critical insights. You will work closely with analysts, engineers, and cross-functional teams to develop reliable datasets that support strategic decision-making. With significant ownership over your projects, you'll design, automate, and optimize data collection workflows while ensuring data quality and reliability. The environment encourages innovation, collaboration, and continuous learning, giving you the freedom to experiment with new technologies and improve existing processes. If you enjoy solving complex data challenges and building automation at scale, this role offers an excellent platform to make a meaningful impact.

As a Data Engineer specializing in web scraping, you will design, develop, and maintain automated data collection systems while ensuring the quality, accuracy, and availability of large-scale datasets. You will collaborate across teams to build efficient, reliable, and scalable data solutions.

• Collaborate with analysts and stakeholders to understand data requirements and deliver tailored data solutions.
• Design, develop, and maintain web scrapers for a wide range of structured and unstructured data sources.
• Clean, transform, validate, and manipulate large datasets using Python and Pandas.
• Build and maintain data ingestion pipelines into databases or data warehouses.
• Schedule, monitor, and optimize scraping workflows using orchestration tools such as Apache Airflow.
• Develop quality control checks to ensure data integrity, consistency, and availability.
• Investigate and resolve data pipeline issues and time-sensitive production incidents.
• Design and enhance internal tools, automation frameworks, and platform capabilities to improve operational efficiency.
• Work closely with cross-functional engineering teams to implement scalable and maintainable data processing workflows.

The ideal candidate combines strong software engineering skills with hands-on experience in web scraping, data processing, and automation. Success in this role requires both technical expertise and a proactive, problem-solving mindset.

• Bachelor's or Master's degree in Computer Science or a related technical discipline.
• 2–4 years of professional software development experience.
• Strong programming skills in Python and solid SQL/database knowledge.
• Advanced experience using the Pandas library for data cleaning, transformation, and analysis.
• Experience working with web technologies, including HTML, JavaScript, APIs, and related protocols.
• Proven experience processing, cleaning, and transforming large datasets.
• Familiarity with web scraping frameworks and tools such as Selenium, Scrapy, XPath, Fiddler, or Postman.
• Experience with workflow orchestration tools such as Apache Airflow or similar platforms.
• Knowledge of Docker containerization; Kubernetes experience is an advantage.
• Familiarity with CI/CD tools such as Jenkins or GitLab CI/CD.
• Experience working with cloud services, particularly AWS technologies such as S3, RDS, Lambda, SNS, or SQS, is preferred.
• Strong analytical thinking, attention to detail, communication skills, and a passion for automation and continuous improvement.

• Opportunity to work on challenging projects supporting a leading global asset management environment.
• High level of ownership and autonomy in a collaborative, team-oriented culture.
• Exposure to modern data engineering, web scraping, cloud, and automation technologies.
• Collaborative environment with experienced engineering, product, and data professionals.
• Opportunities for continuous learning, professional growth, and technical skill development.
• Merit-driven culture that values innovation, initiative, and individual contributions.
• Flexible, technology-focused environment with opportunities to work on impactful data products.