Employer description & source details
Experience with retailer, marketplace, digital-commerce, or digital-shelf data. Experience operating cloud-based services and automated data-processing workflows. Familiarity with anti-bot techniques, headless browsers, scraper observability, data-quality controls, and resilient extraction patterns. Experience improving team operating rhythms, delivery metrics, incident practices, and engineering productivity. Experience hiring and scaling engineering teams. The team has clear priorities, strong engagement, effective coaching, and reliable execution. Scraping services become more predictable, observable, maintainable, and resilient. New and changed data sources are delivered with appropriate quality controls and operational readiness. Stakeholders have timely visibility into delivery status, capacity, risks, and trade-offs. Technical debt and recurring operational issues are systematically reduced. NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding
Extracted skills: javascript, python, java, c#, artificial intelligence, customer success, security, operations