Lead Data Specialist (German) – ML Data Ops at Amazon | Job Opportunity in Gurugram
Description
Join Amazon as a Lead Data Specialist (German) in ML Data Ops in Gurugram. Leverage your expertise in data annotation, German language, and process optimization to drive AI/ML initiatives. Apply today for this full-time opportunity!
About Amazon
Amazon is a global leader in e-commerce, cloud computing, AI, and digital streaming, guided by four key principles:
- Customer Obsession over competitor focus
- Passion for Invention
- Commitment to Operational Excellence
- Long-term Thinking
With a presence in over 100 countries and innovation at its core, Amazon offers unparalleled opportunities to work on transformative technologies, including AI, ML, and large-scale data platforms.
Role Overview
Amazon’s Search Operations (Search Ops) team is looking for a Lead Data Specialist (German) in Machine Learning Data Operations for its Gurugram office. This role supports Amazon’s Search Services by improving AI/ML models that power product search and discovery.
You’ll lead a team of 30–40 associates, ensuring high-quality data annotation, process standardization, and performance improvement. Proficiency in German language (B2 level or higher) is essential for this role.
This is a full-time, permanent position for professionals with 1–6 years of experience in data operations, quality assurance, and team leadership.
Key Responsibilities
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Team Leadership
- Oversee 30–40 associates working on data annotation projects
- Mentor, train, and coach team members on operational processes
- Drive team engagement and track performance metrics
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Operational Excellence
- Ensure quality assurance and productivity standards are met
- Define SOPs (Standard Operating Procedures) and work instructions
- Optimize utilization and manage workload distribution
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Data Analysis & Reporting
- Conduct deep-dive analysis to identify trends, root causes, and solutions
- Generate and present reports to mid and senior-level leadership
- Support Correction of Error (COE) documentation with insights and recommendations
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Stakeholder Collaboration
- Coordinate with cross-functional stakeholders including ML science teams
- Align process improvements with business goals and strategic initiatives
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Quality Assurance
- Perform quality checks on labeled data
- Ensure adherence to annotation guidelines and data integrity
- Handle sensitive data (e.g., adult content, religious topics) with confidentiality
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Process Onboarding and Launch
- Onboard new projects and ensure smooth integration
- Develop launch plans for new hires
- Monitor progress and provide feedback for improvements
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Escalation & Issue Resolution
- Manage escalations effectively
- Analyze escalated data and provide timely resolutions
- Identify process gaps and implement preventive actions
Required Skills
- Proficiency in German (B2 level or above): Verbal, written, and reading comprehension
- Leadership: Experience managing or mentoring teams
- Data Analysis: Intermediate knowledge of data trends and root cause analysis
- Tools: MS Excel (intermediate level), data annotation tools
- Communication: Excellent written and spoken English
- Attention to Detail: Ability to manage competing priorities effectively
Eligibility Criteria
- Education: Bachelor’s Degree in any discipline
- Experience: 1–6 years in roles such as Data Specialist, Quality Analyst, or Subject Matter Expert
- Language Proficiency: German (B2 level or above)
- Location: Gurugram, India
- Employment Type: Full-Time, Permanent
Preferred Qualifications
- Experience with AI/ML data ops, especially in Search or E-commerce domains
- Certification or advanced training in data analytics
- Familiarity with process improvement methodologies like Six Sigma
- Hands-on experience with annotation tools or platforms
- Strong stakeholder management and reporting experience
Why Join Amazon?
🌍 Global Impact
Be part of a mission that improves the search experience of millions of Amazon customers globally.
🤖 Innovate with AI/ML
Work alongside machine learning and computer vision experts in refining cutting-edge technologies.
🧑🏫 Career Development
From mentorship and training to career advancement programs, Amazon supports your professional growth.
💼 Inclusive Culture
Join a workplace that celebrates diversity and encourages innovation.
💰 Competitive Compensation
Enjoy Amazon’s industry-leading compensation packages with benefits.
Location Details
📍 Gurugram, Haryana, India
Amazon’s Gurugram office is a hub of innovation and technology, offering world-class facilities, collaborative workspaces, and easy accessibility.
Note: This role may involve a hybrid work model depending on project requirements.
Application Process
- Visit the Amazon Jobs Portal
- Search for the Job Title: Lead Data Specialist (German), ML Data Ops
- Upload Resume & Cover Letter
- Language Proficiency Test (German)
- Technical Assessment (if applicable)
- Interviews: Includes rounds with hiring managers and peer teams
- Offer Letter & Onboarding
🚨 Apply early! 119 applicants have already applied.
CTA – Apply Now
🎯 Ready to level up your career at Amazon?
Apply today to become a part of a team that is shaping the future of machine learning and search at Amazon.
🔗 Apply Now on Amazon’s Career Portal
📤 Share this opportunity with friends who are fluent in German and looking to make a difference in tech!
Frequently Asked Questions (FAQs)
❓ What is the salary range?
While the exact package isn’t disclosed, Amazon offers industry-competitive compensation based on experience and skills.
❓ Is German proficiency mandatory?
Yes, B2 level or higher proficiency in German is a must (speaking, reading, writing, and comprehension).
❓ What kind of data will I work with?
You’ll work with labeled and unlabeled data related to customer queries, products, search results, and images, including some sensitive content.
❓ Can freshers apply?
This role requires 1–6 years of relevant experience, preferably with leadership exposure.
❓ Are remote work options available?
This is primarily an on-site role in Gurugram, though flexibility may depend on business needs.
