Zyte Benefits Overview

The Data QA Engineer designs and owns quality approaches for customer data projects, combining manual, visual, exploratory, and automated testing. Responsibilities include validating extracted data, analyzing completeness and accuracy with statistics and charts, documenting defects, producing quality reports, clarifying requirements, and improving QA tooling and processes. The role collaborates with developers, project managers, clients, and QA leadership in an agile environment, using Python, Pandas, Jupyter, SQL, web technologies, and REST API testing.

Build and operate an internal agentic AI platform, integrating SaaS systems, APIs, data, permissions, and MCP tools. Develop production AI agents with retrieval, embeddings, evaluation, tracing, and cost optimization. Deploy cloud-based internal tools, establish AI development standards, support adoption across teams, and collaborate with technical and non-technical users.

Manage Zyte’s developer and enterprise event strategy, including event selection, sponsorships, speaking opportunities, Extract Summit US and EMEA, logistics, vendors, budgets, registrations, lead handoff, and CRM reporting. Partner with Sales, DevRel, Engineering, Product, and Marketing to execute events and measure pipeline impact. Travel is required for flagship and selected external events.