Business Intel Engineer I

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 I 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
As a Business Intelligence Engineer at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with massive-scale data and providing analytic support to product/program managers, engineers using these data. You will utilize your deep expertise in business analysis, metrics, reporting, and analytic tooling/languages like SQL, Excel, Python and others, to translate the data into meaningful insights. You will have ownership of the insights you are building for the business, and will play an integral role in tactical decision-making for critical risk areas.

Build self-service tools and dashboard that not only gives aggregated metrics but also provide ways to pull granular data for defect verification, customer communication, deep-dives, etc.
Perform deep-dives and data analysis. Provide recommendation on new metrics or business decision.
Mentor teammates, provide inputs in team and org level strategic planning, lead cross org discussions

About the team
Here's an expanded version of the rephrased text:

The International Seller Services Central Analytics (ISS-CA) team is a highly specialized, cross-functional group tasked with driving critical business insights and breakthroughs. Composed of experts from diverse backgrounds, including scientists, economists, Business Intelligence Engineers, Data Engineers, and Business Analysts, this team is at the forefront of leveraging massive-scale data, advanced analytics, and machine learning techniques.

Our mission is twofold - first, to uncover revolutionary leaps forward in understanding the behavior and performance of third-party (3P) sellers on the platform. By tapping into the vast troves of data available, the ISS-CA team applies their formidable analytical capabilities to extract deep, actionable insights that can inform and optimize the seller experience.

Secondly, the team plays a pivotal role in guiding strategic business decisions through their data-driven approach. Their work provides the foundation for evidence-based actions that can propel the platform and its seller ecosystem to new heights of success. Whether it's identifying emerging trends, uncovering hidden growth opportunities, or optimizing operational efficiency, the ISS-CA team's insights are invaluable in shaping the future direction of the business.

With their cross-functional expertise and relentless pursuit of innovation, the ISS-CA team is at the forefront of leveraging the power of data and advanced analytics to revolutionize the way the platform engages with and supports its third-party seller community.

Basic Qualifications:
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with scripting language (e.g., Python, Java, or R)
- Experience gathering business requirements, using industry standard business intelligence tool(s) to extract data, formulate metrics and build reports
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience

Preferred Qualifications:
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design

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