Data Quality Specialist - German, AGI Data Services - G T Quality

AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. Amazon is investing in generative AI and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us.

We are looking for those candidates who just don’t think out of the box, but make the box they are in ‘Bigger’. The future is now, do you want to be a part of it? Then read on!

Quality Specialists play a vital role in establishing and maintaining comprehensive quality frameworks across our operations.

Key job responsibilities

• Define and implement quality metrics for established workflows
• Create prescriptive actions for quality issues
• Partner with customers, operations and internal support teams to optimize workflow quality
• Conduct side-by-sides to identify opportunities for workflow enhancement and quality improvements
• Analyze data trends and develop solutions
• Monitor quality performance and coach operations teams
• Create and maintain quality metrics reports
• Handle customer escalations and recommendations
• Evaluate and suggest improvements for quality tools
• Support process documentation and implementation

A day in the life Primary responsibility begins with developing robust quality strategies in collaboration with customers and CPMs, encompassing metrics, audit approaches, and specific targets for each workflow. When quality issues arise, these specialists create prescriptive actions, examining data patterns to formulate effective solutions. They maintain a continuous improvement cycle by managing a critical feedback loop between operations and customers, drawing insights from multiple sources including quality auditors, side-by-side observations, and metric analysis. Through regular side-by-side sessions, they identify opportunities for workflow enhancement and quality improvements. The specialists serve as key escalation points for customer concerns, providing strategic recommendations based on their deep understanding of processes. They consistently evaluate quality tools, suggesting refinements to enhance effectiveness, while simultaneously maintaining and updating process documentation to ensure standardization and clarity across all workflows. This comprehensive approach ensures quality remains at the forefront of our operational excellence. Basic Qualifications: - Speak, write, and read fluently in German

• Advanced-level proficiency in German language (C1+ or equivalent fluency by Common European Framework of Reference for Languages (CEFR) standards)
• Intermediate-level proficiency in English (B2+ or equivalent fluency by CEFR standards)
• 1+ years of experience in a quality assurance, quality control, or data quality role
• Experience defining, tracking, and reporting quality metrics or KPIs
• Strong analytical and problem-solving skills with the ability to identify root causes and develop prescriptive actions
• Experience working with data to identify trends, patterns, and quality issues
• Ability to create and maintain process documentation, SOPs, or quality guidelines Preferred Qualifications: - Bachelor's degree in a relevant field (e.g., Linguistics, Data Science, Business, or related discipline)
• Experience applying structured quality methodologies (e.g., DMAIC, 5 Whys, Fishbone/Ishikawa analysis, or Six Sigma principles)
• Experience partnering with cross-functional stakeholders (operations, customers, or program managers) to drive quality improvements
• Demonstrated ability to build or improve quality frameworks, audit processes, or feedback loops
• Experience coaching or providing quality feedback to operations or associate-level teams
• Proficiency in data analysis tools (e.g., Excel, SQL, or BI tools) to support quality reporting and trend analysis
• Ability to adapt to fast-paced environments with evolving workflows, priorities, and quality targets
• Experience in machine learning data operations, annotation quality, or content review workflows