Data Engineer - Amazon FinTech
Amazon.com
Are you a highly skilled data 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 organizations. 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.
As a Data Engineer in this team you will build and enhance the businesses global financial systems org wide. The primary product used is TM1, but unlike other FinTech teams you will have the freedom to use Amazon's full arsenal of AWS technology to build the innovative solutions required to deliver at the scale a trillion dollar company demands. You will manage all aspects from requirements gathering, technical design, development, deployment, and integration to solve budgeting, planning, performance management and reporting challenges.
Key job responsibilities
- Design and implement next generation financial solutions assisted by almost unlimited access to AWS resources including EC2, RDS, Redshift, Stepfunctions, EMR, Lambda and 3rd party software TM1.
- Build and deliver high quality data pipelines capable of scaling from running for a single month of data during month end close to 150 and more months when doing restatements.
- Continually improve ongoing reporting and analysis processes and infrastructure, automating or simplifying self-service capabilities for customers.
- Dive deep to resolve problems at their root, looking for failure patterns and suggesting and implementing fixes or enhancements.
- Prepare runbooks, methods of procedures, tutorials, training videos on best practices for global delivery.
- Solve unique challenges presented by the massive data volume and diverse data sets working for one of the largest companies in the world.
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 organizations. 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.
As a Data Engineer in this team you will build and enhance the businesses global financial systems org wide. The primary product used is TM1, but unlike other FinTech teams you will have the freedom to use Amazon's full arsenal of AWS technology to build the innovative solutions required to deliver at the scale a trillion dollar company demands. You will manage all aspects from requirements gathering, technical design, development, deployment, and integration to solve budgeting, planning, performance management and reporting challenges.
Key job responsibilities
- Design and implement next generation financial solutions assisted by almost unlimited access to AWS resources including EC2, RDS, Redshift, Stepfunctions, EMR, Lambda and 3rd party software TM1.
- Build and deliver high quality data pipelines capable of scaling from running for a single month of data during month end close to 150 and more months when doing restatements.
- Continually improve ongoing reporting and analysis processes and infrastructure, automating or simplifying self-service capabilities for customers.
- Dive deep to resolve problems at their root, looking for failure patterns and suggesting and implementing fixes or enhancements.
- Prepare runbooks, methods of procedures, tutorials, training videos on best practices for global delivery.
- Solve unique challenges presented by the massive data volume and diverse data sets working for one of the largest companies in the world.
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