Business Intelligence Engineer II, Selling Partner Financial Tech

Are you passionate about working with Amazon-scale data systems solving critical analytical problems and delivering mission-critical insights Does the idea of building end-to-end business intelligence solutions that will delight millions of Selling Partners excite you If yes then we want to talk with you. Selling Partner Financial Technology (SPFT) is looking for a dynamic Business Intelligence Engineer to join our financial experiences team to deliver world-class data-driven insights that delight our Selling Partners.

Selling Partners depend on us to provide accurate and transparent financial information to help them manage and grow their business. We are looking for Business Intelligence Engineers with a strong sense of ownership and a passion for delivering creative analytical solutions for complex problems on an unprecedented scale. As part of the team you will have opportunity to have a significant impact on our systems our business and most importantly our customers and build solutions that will achieve our vision of 100% financial accuracy and transparency.

Key job responsibilities
As a Business Intelligence Engineer II at Amazons SPFT organization you will work with massive-scale data to provide analytic support to product/program managers and engineers. Leveraging deep expertise in business analysis metrics reporting and analytic tooling including SQL Excel and Python you will translate complex data into meaningful insights that drive tactical decision-making for critical risk areas. You will own the insights you build for the business playing an integral role in strategic planning and operational excellence.

Your responsibilities include building self-service tools and dashboards that deliver both aggregated metrics and granular data capabilities for data verification stakeholder and customer communication and deep-dive analysis. You will perform comprehensive data analysis identify trends and anomalies and provide recommendations on new metrics and business decisions that impact product development and operational strategy. Additionally you will mentor teammates on BI best practices contribute to team and organizational strategic planning and lead cross-organizational discussions to influence data-driven decision-making across Amazons business functions.

A day in the life

Collaborate with experienced cross-disciplinary Amazonians to conceive design and bring innovative BI solutions that support financial experience initiatives

Build self-service tools and dashboards that not only provide aggregated metrics but also enable granular data extraction for deep-dives and root cause analysis

Design and implement scalable BI solutions in a large distributed computing environment working with massive datasets to deliver insights at incredible scale and speed

Perform deep-dive data analysis to identify trends anomalies and opportunities; provide recommendations on new metrics business decisions and process improvements

Translate functional requirements into robust scalable supportable analytical solutions that work well within the overall system architecture

Create solutions for predictive analytics and automated reporting systems with exposure to innovative technologies supporting vendor payment accuracy and dispute resolution

Participate in the full development cycle end-to-end from design implementation and testing to documentation delivery and maintenance of BI artifacts

Produce comprehensive usable documentation for dashboards metrics definitions data lineage and analytical methodologies

Evaluate and make decisions around the use of new or existing analytical tools data visualization platforms and BI technologies

Use generative AI tools to automate query generation debug code create documentation and accelerate data analysis workflows

Mentor teammates on BI best practices provide inputs in team and org-level strategic planning and lead cross-org discussions to influence data-driven decision-making

- 3 years of analyzing and interpreting data with Redshift Oracle NoSQL etc. experience
- Experience with data visualization using Tableau Quicksight or similar tools
- Experience with data modeling warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

- Experience with AWS solutions such as EC2 DynamoDB S3 and Redshift
- Experience in data mining ETL etc. and using databases in a business environment with large-scale complex datasets

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