Senior Software Engineer (Web Scraping, Data acquisition, Data collection)

At NIQ Digital shelf, scraping isn’t just about collecting data, it’s about outsmarting the obstacles that stand in the way of visibility. Every day, we process tens of billions of data points from thousands of sources, both web and mobile, and transform them into actionable insights for the world’s top retailers and brands.
You'll join a team of 60+ scrapers , engineers, analysts, and data lovers from across the globe. As part of our scraping and R&D team, you’ll have space to experiment, push boundaries , and bring bold ideas to life. You’ll collaborate closely with Customer Success , Operations , and Data to ensure we extract high-quality, actionable data — fast and at scale.
This isn’t just a coding job. You’ll need to think like a hacker , move like an engineer, and act like an inventor

Responsibilities

Design and build distributed scraping architectures that can scale across thousands of domains.; Reverse engineer APIs and mobile apps using tools like Frida , mitmproxy , Charles Proxy, burp and many more.; Detect common anti-bot measures (like JavaScript checks or browser behavior detection) to build crawlers that adjust to appear more human-like.; Lead technical innovation in scraping: identify edge cases, prototype new approaches, and share knowledge with the team.; Set up anomaly detection and monitoring to detect blockers or failures early

Requirements

What You Bring; 5+ years of experience with Python and large-scale scraping projects.; Deep understanding of anti-bot technologies and how to bypass them, fingerprinting, WAFs, JavaScript challenges, etc.; Experience working with Scrapy , Requests , httpx , Selenium , Playwright , or custom headless browser drivers.; Skilled at handling proxies (residential, datacenter, rotating), session management, cookie injection, and TLS tweaking.; Strong debugging skills across browser, HTTP traffic, and device-level interactions.; You think independently and enjoy solving problems no one has solved before.; Familiarity with structured storage formats (Parquet, Avro), or real-time stream processing.; Good knowledge of databases like MongoDB, InfluxDB, and Redis, including how they work and how to optimize them. ➕ Bonus Skills; Experience with real-device simulation for mobile scraping.; Comfortable building and maintaining distributed task queues (Celery, Kafka, etc.).; Experience scraping high-security platforms or mobile-first environments.; Exposure to Linux or cloud environments (AWS, GCP, etc.).; Basic understanding of Kubernetes, Cloud Run, and Cloud Functions to deploy and orchestrate scraping workloads.