Senior Data Infrastructure Engineer (Scraping & Scale)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Infrastructure Engineer (Scraping & Scale) based in Saudi Arabia. We are seeking a Senior Data Infrastructure Engineer to design and scale high-performance web scraping and data ingestion systems. In this fully remote role, you will build the core infrastructure responsible for collecting millions of social media profiles, posts, and video records daily. You will tackle complex anti-bot challenges, develop resilient distributed pipelines, and ensure reliable data delivery at scale. Working at the intersection of data engineering, automation, and AI infrastructure, you will support large-scale analytical and machine learning workflows. This opportunity is ideal for an engineer who combines deep technical expertise with a strong focus on performance, reliability, and continuous improvement. Accountabilities The Senior Data Infrastructure Engineer will lead the development and maintenance of scalable data collection systems, ensuring reliable ingestion, efficient orchestration, and high-quality data availability for downstream applications. • Design and manage web scraping infrastructure using residential proxy networks, TLS fingerprinting, browser automation, and session rotation. • Build fault-tolerant, high-throughput scraping pipelines to collect data from Instagram, TikTok, YouTube, X, and other web sources. • Develop distributed queues and workflow orchestration systems using technologies such as Temporal, Ray, Apache Kafka, and Celery. • Architect storage environments for structured and unstructured data using Parquet, Apache Iceberg, Snowflake, and Amazon S3. • Implement monitoring, automated alerts, and recovery mechanisms to identify platform changes, blocking patterns, and proxy failures. • Maintain reliable data ingestion at scale while minimizing downtime and supporting daily processing of millions of records. • Enable downstream AI and analytics workflows through robust, well-structured data infrastructure. Requirements The ideal candidate brings substantial experience in web scraping, data engineering, or reverse engineering, along with strong programming skills and expertise in distributed systems and data storage technologies. • At least 4 years of experience in high-volume web scraping, data engineering, or reverse engineering. • Strong experience handling advanced anti-bot systems, including Cloudflare, Akamai, and PerimeterX, using TLS impersonation, browser automation, and proxy management. • Advanced proficiency in Python or Go. • Extensive experience with browser automation and scraping frameworks such as Playwright, Puppeteer, Scrapy, or Selenium. • Practical knowledge of distributed systems and task queues, including Temporal, Ray, Kafka, and Redis. • Strong SQL skills and experience with modern analytical data lakes and data warehouses. • Ability to design scalable, fault-tolerant systems and troubleshoot complex data ingestion challenges. Preferred Qualifications • Experience extracting short-form video content and user metadata from TikTok, Instagram, and YouTube. • Experience integrating scraping outputs with vector databases and real-time AI processing queues. Benefits • Fully remote work arrangement. • Full-time employment. • Salary, healthcare coverage, paid leave, and additional benefits are not specified in the provided job description. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Show more Show less

The ideal candidate brings substantial experience in web scraping, data engineering, or reverse engineering, along with strong programming skills and expertise in distributed systems and data storage technologies. At least 4 years of experience in high-volume web scraping, data engineering, or reverse engineering. Strong experience handling advanced anti-bot systems, including Cloudflare, Akamai, and PerimeterX, using TLS impersonation, browser automation, and proxy management. Advanced proficiency in Python or Go. Extensive experience with browser automation and scraping frameworks such as Playwright, Puppeteer, Scrapy, or Selenium. Practical knowledge of distributed systems and task queues, including Temporal, Ray, Kafka, and Redis. Strong SQL skills and experience with modern analytical data lakes and data warehouses. Ability to design scalable, fault-tolerant systems and troubleshoot complex data ingestion challenges.

Design and manage web scraping infrastructure using residential proxy networks, TLS fingerprinting, browser automation, and session rotation. Build fault-tolerant, high-throughput scraping pipelines to collect data from Instagram, TikTok, YouTube, X, and other web sources. Develop distributed queues and workflow orchestration systems using technologies such as Temporal, Ray, Apache Kafka, and Celery. Architect storage environments for structured and unstructured data using Parquet, Apache Iceberg, Snowflake, and Amazon S3. Implement monitoring, automated alerts, and recovery mechanisms to identify platform changes, blocking patterns, and proxy failures. Maintain reliable data ingestion at scale while minimizing downtime and supporting daily processing of millions of records. Enable downstream AI and analytics workflows through robust, well-structured data infrastructure.