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Description

Prime Video is an industry leading, high-growth business and a critical driver of Amazon Prime subscriptions, which contribute to customer loyalty and lifetime value. Prime Video is a digital video streaming and download service that offers Amazon customers the ability to rent, purchase or subscribe to a huge catalog of videos.

This is a high visibility role, within video content research org in Prime Video Finance, who will focus on supporting marketing measurement work stream. As a Data Engineer, you will be working in one of the world's largest and most complex data warehouse environments.

You will design, implement and support scalable data infrastructure solutions to integrate with multi heterogeneous data sources, aggregate and retrieve data in a fast and safe mode, curate data that can be used in reporting, analysis, machine learning models and ad-hoc data requests.

You will be exposed to cutting edge AWS big data technologies. You will also have the opportunity to create white papers and build POCs. In this role, you will have the opportunity to build complex, high-performing, and scalable data products.

In this role you will help scientists collect the latest worldwide video data, customer segments, and diverse signals of marketing impressions to support scaled forecasting tools. You will be working with a diverse group of economists and machine-learning researchers in a fun-filled working environment on projects like the following:

The team needs to measure incremental impact of our marketing investments.

The team needs to predict how many customers will watch any new show that Amazon Studios is considering creating. We build complex data products to provide insights into customer segments worldwide and to support scaled forecasting tools.

The team measures and forecasts the performance of our marketing campaigns--how many new customers will our advertising dollars drive? We collect diverse signals of marketing impressions and publish model output for driving key business decisions.

How effective are Amazon Originals at attracting new Prime members and helping customers discover other Prime benefits? We build tools that measure the long-run value driven by customer engagement with our content.

Key job responsibilities

Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL/python and AWS big data technologies such as EMR, Redshift.

Explore and learn the latest AWS technologies to provide new capabilities and increase efficiencies.

Designing and implementing complex ETL pipelines by processing petabytes of data that empowers scientists in team to build large scale Machine Learning models.

Work closely with Product Managers, Applied Scientists, and Economists in team to explore new data sources and build pipelines for same that expands existing ML models. Partner with cross teams in amazon and external to unblock team with data needs.

Design and build Data products such as data-quality, anomaly detection and data governance.

About the team

The mission of the Video Content Research team is to provide analytics and science to support customer-driven content decisions. We are product focused, so we build reliable, scalable, worldwide tools. We measure the long-run economic value of Prime Video, and we help define the strategies and support decisions to maximize this value. Our team values close collaboration, and we strive to constantly learning new machine-learning and cloud-computing technologies.

Basic Qualifications

• 2+ years of data engineering experience

• Experience with SQL

• Experience with data modeling, warehousing and building ETL pipelines

• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)

• Experience with one or more scripting language (e.g., Python, KornShell)

Preferred Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR

• Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

• Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

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 $91,200/year in our lowest geographic market up to $185,000/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.