Prime Video offers customers a vast collection of movies, series, and sports all available to watch on hundreds of compatible devices.
U.S. Prime members can also subscribe to 100+ channels including Max, discovery+, Paramount+ with SHOWTIME, BET+, MGM+, ViX+, PBS KIDS, NBA League Pass, MLB.
TV, and STARZ with no extra apps to download, and no cable required. Partner experience (PX) organization obsess over partners with a focus on delivering world-class partner tools to enable them to launch, grow and scale their businesses across PV’s business lines.
PX organization build various products to enable partners to 1) onboard and make their selection available to customers globally;
2) manage selection across PV business lines 3) acquire, engage, retain customers through self-service marketing, merchandising, promotion tools.
By providing partners with best-in-class self-service capabilities throughout their engagement with Amazon, we power the flywheel through increased partner satisfaction and expanded the breadth of selection available to Amazon customers.
PXBI (Partner Experience BI team) fulfills data needs for Partner Experience (PX) organization to provide big data to power reporting functions across five crucial partner-facing products, meeting reporting contractual obligations and powering Prime Video partners with performance data for measurement to grow their business in Prime Video;
also build data pipelines to enable data to measurement effectiveness of organization’s product deliveries and facilitate data-driven decision-making within PX organization.
Key job responsibilities
We are seeking a talented Sr. Data Engineer to enhance overall PXBI core data infrastructure by implementing AWS services to build the data pipelines, enhancing data accuracy, reducing data latency, increasing data service stability, and ensuring compliance with Amazon-wide data compliance regulations, Furthermore, the Sr Data engineer partner with SDE team to build Slate analytics product a new generation of reporting and analytics product to replace the existing VC reporting system and PVD reporting system.
We will design and implement data lake to provide robust, scalable data infrastructure to deliver intra-day data to power slate analytics product.
As a Sr. Data Engineer in the team, you will work on very large data sets in one of the world's largest and most complex data lake and data warehouse environments.
You will design, build and maintain the robust data infrastructures to process large volumes of data (big data) from various sources.
This includes writing clean, maintainable code that adheres to best practices, being familiar with AWS data processing services, possessing broad knowledge of when to utilize different types of data, and understanding data security and compliance standards to ensure alignment with company policies and regulations.
A day in the life
Write the design document to propose the solutions to resolve challenging data processing and data handling.
Meet with your peers to discuss the solutions.
Review your design doc with product managers, senior management, Sr SDE to communicate your thought and gather their feedback.
Build up data infrastructure and data pipelines by using AWS services.
Productionalize your solutions into products which will be used by WW Prime Video partners.
About the team
We are a centralized data team to support partner experience organization. We process big data by using advance AWS services.
We work closely with PM, TPM, SDE, collaborate with other data teams outside of partner experience organization to deliver products for Prime Video partners.
We are open to hiring candidates to work out of one of the following locations :
Culver City, CA, USA Seattle, WA, USA
BASIC QUALIFICATIONS
- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
PREFERRED QUALIFICATIONS
- Experience with big data technologies such as : Hadoop, Hive, Spark, EMR
- Experience operating large data warehouses
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