Data Science Software Engineer at Amazon

📌 🏷️ Full Time 🕑 2021-06-16
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Senior Data Engineer

Amazon Advertising is dedicated to driving measurable outcomes for brand advertisers, agencies, tool providers, authors, and entrepreneurs. Our ad solutions-including sponsored, display, video, and custom ads-leverage Amazon's innovations and insights to find, attract, and engage intended audiences throughout their daily journeys. With a range of flexible pricing and buying models, including self-service, managed service, and programmatic ad buying, these solutions help businesses build brand awareness, increase product sales, and more. Global Advertising Partner Development team is looking for an experienced, self-driven, analytical, and strategic Data Engineer to build the next generation of data and insights for Amazon advertisers and brands. In this role, you should have deep expertise in the design, creation, and management of large and complex datasets. You should have strong experience at building scalable solutions to flow huge amounts of data from production systems into the data lake. You should be able to design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science teams. You will work closely with the Business Intelligence Engineers, Data Scientists, Product Managers, Software Development teams and other business stakeholders on many unique business problems and use creative problem solving to deliver actionable output in data gathering, transformation, ingestion and storage. You should be able to gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture. As a Senior Data Engineer, you will also be mentoring other junior resources, provide technical leadership, lead data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective.
BASIC

QUALIFICATIONS

- 5 years of experience as a Data Engineer or in a similar role
- Experience with data modeling, data warehousing, and building ETL pipelines
- Experience in SQL - Excel in the design, creation, and management of large datasets.
- Detailed knowledge of cloud-based data warehouses, architecture, infrastructure components, ET
L and reporting/analytic tools and environments.
- Skilled with writing, tuning, and troubleshooting complex SQL queries
- Experience with Big Data technologies such as Hive/Spark, AWS EMR, AWS Glue, AWS Lambda , Kinesis, Redshift.
- Proficiency in one of the scripting languages - python, java or similar.
- Strong organizational skills and planning prowess, with excellent attention to detail.
PREFERRED

QUALIFICATIONS


- 7-10 years of industry experience as a Data Engineer or related specialty (e.g. Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets
- Experience with Massively Parallel Processing (MPP) databases
- Redshift, Teradata etc
- Experience with distributed systems and NoSQL databases
- Experience leading medium to large-scale data warehousing and analytics projects, including using AWS technologies
- Redshift, S3, EC2, Data-pipeline and other big data technologies
- Excellent communication skills and able to work with business owners to develop and define key business questions and to build data sets that answer those questions
- Experience providing technical leadership and mentorship to engineers and scientists on best practices in the data engineering space
- Be self-driven and show ability to deliver on ambiguous situations and projects This position can be located in New York City or Seattle. 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.

View Application

You will be redirected to Amazon's preferred application process.

You will be redirected to Amazon's preferred application process.

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