Data Engineer II
Content + Source + Freshness • 14 Dec 2025 • 95% confidence
Offer value
Balanced offering due to the blend of technical challenges and opportunities for impactful data-driven decision-making.
- Engage with large-scale data-driven operations
- Contribute to solutions that impact seller performance
- Growth in data engineering skills and career advancement
Pros
- Chance to work with large-scale data solutions
- Involvement in meaningful projects that support sellers
- Opportunity for cross-functional collaboration
Cons
- Competition for performance metrics may be intense
- Position may require long hours during peak times
- Complexity of data systems can lead to high stress
Who it's for
Mid-level • Hybrid / office
Good fit
- Experienced data engineers
- Professionals passionate about analytics
- Candidates who thrive in collaborative environments
Not recommended for
- Entry-level candidates without technical skills
- Individuals preferring minimal teamwork
- Those resistant to handling large datasets
Motivation fit
Key skills
About the job
Description
Join us in the International Seller Services Central Analytics Team and Tackle Data Warehousing and Reporting Challenges!
We are a dedicated group of BIE, DE, DS, AS and BAs within the Seller Services organization at Amazon. Our mission is to deliver data-driven analytical solutions that empower sellers to thrive on Amazon's global platform. We specialize in constructing and maintaining intricate standard data pipelines that are used by thousands of users across the globe to measure, derive and analyze performance of the sellers selling on Amazon.
We are currently in search of a brilliant, self-driven, and seasoned BIE III to join our team. In this role, you will have the opportunity to work on building scalable solutions, including extensive data models and complex ETL pipelines and utilize your expertise to raise the bar on data timeliness, discoverability and availability of the same.
Key job responsibilities
• Design and implement scalable, secure data pipelines and infrastructure using AWS technologies and big data tools
• Build and maintain high-performance ETL processes that handle large-scale, complex datasets
• Architect end-to-end analytical solutions that are highly available, stable, and cost-effective
• Transform raw data into actionable insights through effective data modeling and integration
• Implement best practices in data system creation, data integrity, and documentation
• Proactively identify opportunities for process improvement and automation
• Partner with business stakeholders to gather requirements and translate them into technical solutions
