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Amazon
Are you enthusiastic about the standardization of data and the automation of Business Intelligence engineering processes to drive analytics and reporting? Do you excel in fast-paced, ambiguous environments? Are you passionate about transforming data into actionable recommendations, implementing data governance best practices, and defining standards for data access, quality, and consistency? If so, your search ends here! Join us to innovate and deliver world-class business intelligence. Find out more about us in this video: https://www.youtube.com/watch?v=zt1qWl379rM
The Worldwide Operations Finance Standardization & Automation (SnA) Tech team is looking for a customer focused, analytically and technically skilled Business Intelligence Engineer (BIE) to join the team. As part of the transportation operation, Amazon ships several millions of packages every year to customers on time with high customer excellence.
The role demands a comprehensive grasp of data and reporting, requiring an individual with strong analytical capabilities and exceptional business acumen. As a valuable member of the growing BIE team within the central Tech organization supporting WW operations finance, you will play a crucial role in shaping our strategic innovation program. Your contribution will empower project teams with insights into operational performance. The dynamic growth of the business and the evolving complexity of the global transportation network make this position both exciting and challenging. The ideal candidate will not only elevate the standard for data retrieval and analysis but will also exhibit a keen curiosity to understand the business holistically, proactively delving into issues as they arise. Attention to detail, proficiency and advanced skills in SQL/DWH/Python, and a knack for solving data and reporting challenges are essential. Effective collaboration and clear communication with functional teams, both regionally and globally, are integral to the role. The ideal candidate thrives in a fast-paced, dynamic environment, embodying a creative and analytical problem-solving approach, aligning with the Amazon motto to "Work Hard. Have Fun. Make History.".
Key job responsibilities
The ideal candidate is a seasoned data professional with a strong bias for action, possessing expertise in data modeling, ETL, SQL, and scripting. Additionally, they should have a passion for presenting data in a visually appealing and easily digestible manner. In this role, you will play a key part in identifying complex business problems, recognizing opportunities, and implementing solutions to enhance Operations Finance-facing systems, processes, and tools. The successful candidate will be a self-starter and quick learner, comfortable with ambiguity, results-oriented, with a keen attention to detail. They must insist on high standards, demonstrate decision-making abilities, and be ready to adapt in a fast-paced, ever-changing business environment. Your responsibilities will include setting data modeling standards, constructing complex data pipelines, building and maintaining multiple databases, identifying complex/abstract problems, and uncovering insights through the use of statistical, data mining, and visualization techniques. Furthermore, you will contribute to process automation by developing deep-dive tools, user interfaces (UIs), metrics, and dashboards to communicate insights in real-time to business teams. Successful team members collaborate effectively with business customers and cross-functional data management teams to solve problems and implement innovative solutions.
About the team
S&A WW Ops Finance Tech org just started a few months back (Brand new org), having a very strong tech product road map for 2024.- 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
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