Customer Behavior Analytics' Downstream Impact (DSI) team owns Causal Machine Learning products aimed at estimating long-term value and informing financial planning. In this role, you will build big data systems processing several PETA bytes of data. You will influence financial investment forecasting, and how hundreds of billions of dollars will be spent across Amazon businesses.


Key job responsibilities
As a Software Development Engineer in DSI, you will:
- Work in a cross-functional team of product managers, Data Engineers, and Scientists to build causal machine learning systems.
- Build data processing systems on AWS technologies (e.g., S3, EC2, EMR) and Apache Spark to process petabytes of data.
- Apply MLOps principles to facilitate rapid scientific innovation and experimentation.
- Scale machine learning workflows by leveraging deep knowledge of distributed systems like Spark, so that we can scale our systems to handle larger datasets, reduce IMR and computation limits
- Learn about the science of causal inference and lead the implementation of new concepts in production.
- Engage with customers and partner teams to improve product scope and usability.

A day in the life
- A day in the life of SDE in our team includes (but is not limited to) working on architecture designs, brainstorming with other engineers and working with leaders, planning day-week-month, and writing code.
- We prioritize work-life balance and our long-term design commitments have led us to have minimal operational maintenance required, with 90%+ oncall work expected during our business hours.
- We plan our team's delivery using bi-weekly sprint plannings, backlog grooming sessions, weekly demos, and bi-monthly team events.


About the team
We are a team of 9 engineers working together to build causal machine learning systems processing several PETA bytes of data at the Amazon scale. With our recent product launches and recognition from leadership, we have an exciting charter ahead of us for the rest of 2025!