The Automated Profitability Management (APM) team, part of the Selling Partners Services (SPS) organization, improves the long term success of Amazon Retail by driving lower costs, and unlocking new product selection. Our team builds software and machine learning (ML) models to optimize contract negotiations between tens of thousands of vendors offering millions of products and Amazon. We directly influence the end-customer experience worldwide by determining the optimal combination of terms under which Amazon should acquire its inventory. We focus on product costs but also cover supply chain (Who pays the initial shipping costs?), marketing (Should a vendor fund advertising?), reverse-logistics (Who pays for damaged products? What about unsold inventory?) and more. Our mission is to provide to our customers the world's largest product assortment at competitive prices, through long term partnership with our vendors.
We are looking for Data Engineers to drive the development of new Data Science and ML infrastructure to support the scientists in the development of new ML models. You will work closely with scientists, product managers, and software developers to implement and scale your solutions, leveraging AWS tooling but adding additional layers to support internal needs.
Key job responsibilities
In this role, you will be a technical expert with significant scope and impact. You will work closely with a group of Software Engineers, Data Engineers, Product Managers, Scientists, and Business Intelligence Engineers to create the data infrastructure and machine learning environments necessary to drive our team's initiatives.
Our Data Engineer duties & responsibilities will include:
- Design and deliver big data architectures for experimental and production consumption between scientists and software engineering
- Develop the end-to-end automation of data pipelines, making datasets readily-consumable by visualization tools and notification systems.
- Create automated alarming and dashboards to monitor data integrity.
- Create and manage capacity and performance plans.
- Act as the subject matter expert for the data structure and usage.
- Bachelor's degree in Computer Science, Computer Engineering, or a related technical discipline.
- 5+ years of industry experience in Software Development, Data Engineering, Business Intelligence or related field with a solid track record of manipulating, processing, and extracting values from large datasets.
- Experience with data modeling, data warehousing, and building ETL pipelines
- Solid experience using big data technologies (Redshift, Hadoop, Hive, Hbase, Spark, EMR, etc.).
- Skilled with writing, tuning, and troubleshooting SQL queries
- Experience in designing and building scalable data pipelines
- Excellent grasp of software development life cycle and/or agile development environment
- Knowledge and experience with Data Management and Data Storage best practices.
- Strong customer focus, ownership, and ability to deliver results.
- Excellent communication and collaboration skills
- Effective analytical, troubleshooting, and problem-solving skills.
- Masters in computer science, mathematics, statistics, economics, or other quantitative fields.
- Experience working with AWS big data technologies (Redshift, S3, EMR, Glue).
- Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.
- Experience providing technical leadership and educating other engineers for best practices on data engineering.
- Background in Big Data, non-relational databases, Machine Learning and Data Mining is a plus.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
Software and Programming