Data Engineer, DS2-Science & Data Technology team

- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- 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)

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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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. 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.

You are an individual with outstanding analytical abilities, excellent communication skills, good business understanding, and technically savvy. The successful candidate will be an analytical problem solver who enjoys diving into data, is excited about solving ambiguity problems, can multi-task, and can credibly interface between technical teams and business stakeholders.


Key job responsibilities
1. Design, implement and support an analytical data infrastructure using AWS technologies
2. Build robust and scalable data integration (ETL) pipelines using SQL, and AWS data storage technologies like Aurora, Red Shift etc.
3. Design and develop Analytics applications using modern scripting languages (Python, R, PHP, etc) supporting critical business functions.
3. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
4. Lead architecture design and implementation of next generation BI solution
5. Continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.


About the team
Our team's north star is to empower the device software and services organization, along with its business partners, to make accurate and well-contextualized decisions quickly, helping them focus on delivering the best possible device customer experiences. We achieve this by integrating business intelligence and machine learning into human and system decision flows through scalable, configurable, and reusable foundational services.