Data Engineer, Science
hace 2 semanas
3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
The Amazon Devices team designs and engineers high-profile consumer electronics, including the best-selling Kindle family of products. We have also produced groundbreaking devices like Fire tablets, Fire TV, Amazon Dash, and Amazon Echo.
What will you help us create?
**The Team**: How often have you had an opportunity to be a founding member of a team that is solving a significant problem through innovative technology? Would you like to know more about how we are envisioning the use of data analytics, machine learning, AI and linear programming to solve these problems? If this sounds intriguing, then we’d like to talk to you about a role on a new Amazon team that's tackling a set of problems requiring significant innovation and scaling.
We are seeking a Data Engineer with strong analytical, communication and project management skills to join our team. This role will be a key member of a Science and Data technology team based in Guadalajara,MX. Working closely with business stakeholders, software development engineers and scientist colleagues, you will design, evangelize, and implement state-of-the-art solutions for never-before-solved problems, helping Amazon Device to provide customer great products and keep the data secure. You will work with the most complicated data environment, employ right architecture to handle big data and support various analytics use cases, including business reporting, production data pipeline, machine learning, optimization models, statistical models, simulation, etc. Your work will have a direct impact on the day-to-day decision making in the Amazon Devices Sales & Operations Technology, and end customers.
Zapopan, MEX
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
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