Data Quality Specialist
Amazon
Data Quality Specialist
Amazon
Sells products online and rents cloud computing
Quality Specialists play a vital role in establishing and maintaining comprehensive quality frameworks across our operations. Their 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.
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
Your day starts by checking quality dashboards for your assigned workflows — reviewing audit scores, appeal rates, SLA status, and any overnight escalations. You will spend approximately 30% of your time on analysis: reviewing data trends, investigating root causes of quality dips, and creating prescriptive actions for operations teams.
Another 30% goes to stakeholder communication: leading weekly customer meetings, preparing quality reports, and handling escalations. The remaining time is split between process work (updating SOPs, refining audit rubrics, conducting side-by-sides) and calibration activities (aligning audit standards with Senior Quality Auditors and operations teams).
You are measured on: SLA metrics (appeals and batch completion), customer satisfaction, quality improvement trends for your workflows, and documentation quality.
About the team
The Quality Operations team within FAI Data Services ensures that labeled training data meets accuracy and consistency standards before it is used to train Amazon's AI models. Quality Specialists own the quality strategy for assigned workflows, bridging the gap between operations execution and customer expectations.
- Knowledge of advanced English at CEFR level B2/C1
- Advanced-level proficiency in Catalan language (C1+ or equivalent fluency by Common European Framework of Reference for Languages (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
- Experience leveraging technology and implementing lean principles / Six Sigma methodologies to drive process improvements or equivalent
- Experience communicating with a wide range of stakeholders, including colleagues and leadership, or experience with external customer interaction
- Knowledge of at least one data-focused technology tool, such as Python, SQL, Alteryx, Amazon QuickSight, or similar
- Bachelor's degree in a relevant field (e.g., Linguistics, Data Science, Business, or related discipline)
- 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
- 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
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.
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