Amazon

Data Engineer, Alexa Business Telemetry and Decision Science

Bellevue, WA US
USD 118k - 205k
AWS Python Spark Scala SQL
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Description
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- 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.
We are a part of the Alexa Business Telemetry organization. Join the Alexa eXperience Data (AXD) Team!

Are you passionate about driving customer experience (CX) insights through data? We're seeking enthusiastic individuals to be part of the exciting transformation happening within AXD.

The AXD team is on a mission to redefine itself, focusing on manufacturing and delivering data products that drive CX insights. These insights are not just numbers; they're the key to understanding customer behavior, improving forecasting accuracy, and uncovering users' propensity to spend more based on their interactions.

Imagine being part of a team that envisions becoming the producer of comprehensive and complete customer interactions specific to Alexa. Our goal is ambitious but achievable – we're aiming to create a centralized, high-quality, compute platform-agnostic, privacy-aware data lake accessible to all within the Alexa organization.

As a member of our team, you'll have the opportunity to work with cutting-edge technologies and AWS services like Redshift, Lake Formation, Glue, Step Functions, Lambda, Airflow and Elastic Map Reduce (EMR) to build scalable data pipelines that keep pace with the ever-increasing volume of data produced by AWS services.

This is a great opportunity to shape and build the future of data lakes and supporting data products for years to come. If you're ready to make an impact and be part of a dynamic team, join us at AXD and let's redefine the Alexa eXperience Data (AXD) together!



Key job responsibilities
You know and love working with business intelligence tools, can model multidimensional datasets, and can partner with customers to answer key business questions. You will also have the opportunity to display your skills in the following areas:

Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL
Be comfortable with a degree of ambiguity and willing to develop quick proof of concepts, iterate and improve
Manage AWS Resources - Model data and metadata for ad hoc and pre-built reporting
Interface with business customers, gathering requirements and delivering complete reporting solutions
Apply software best practices including coding standards, code reviews, source control management, agile development, build processes, and testing.
Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
Manage numerous requests concurrently and strategically, prioritizing when necessary.
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