Amazon

Business Intelligence Engineer, DaS FinTech

Job Description

Are you a highly skilled Business Intelligence engineer and project leader? Do you think big, enjoy complexity and building solutions that scale? Are you curious to know what you could achieve in a company that pushes the boundaries of modern technology? If you answered yes and you have a background in FinTech you’ll love this role and Amazon’s data obsessed culture.

Amazon Devices and Services Fintech is the global team that designs and builds the financial planning and analysis tools for wide variety of Amazon’s new and established organisations. From Kindle to Ring and even new and exciting companies like Kuiper (our new interstellar satellite play) this team enjoys a wide variety of complex and interesting problem spaces. They are almost like FinTech consultants embedded in Amazon.

This team is looking for high caliber and tested Business Intelligence Engineer (BIE) to enable and improve senior level business decision making. A strategic thinker who combines technical expertise with business acumen to develop and maintain scalable data solutions. You will apply both business and technical acumen in a fast-paced, ambiguous and innovative environment. Our ideal teammate possesses a natural curiosity, sharp analytical skills and is excited to pioneer on behalf of customers.




Key job responsibilities
- Engineer robust, automated reporting systems and dashboards that facilitate data-driven decision making
- Partner with Product and Business teams to capture requirements and deliver analytical solutions
- Execute targeted data analyses and ensure data quality through regular audits
- Create and maintain systems that provide customers with structured, real-time access to their data
- Build and maintain business-critical reports across different time horizons (weekly to annual)
- Analyze complex historical datasets to uncover trends and present actionable insights through clear communications
- Support development teams in building analytics infrastructure for large-scale data analysis and machine learning deployment
- Transform data insights into concrete recommendations for business strategy and product development
- Develop key performance metrics and create business review presentations using visualization tools
- Perform in-depth analysis using advanced SQL and Python programming
- Design and maintain data infrastructure, including ETL pipelines and cloud-based solutions
- Develop comprehensive documentation and training resources for self-service analytics tools- Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
- 5+ years of analysing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualisation using Tableau, Quick sight, or similar tools
- Experience independently leading and delivering end-to-end analytics analyses and products.
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Data infrastructure and automation (such as ETL data pipelines, Redshift, S3, Athena, Glue)
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business


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