Data Engineer

Data Engineer, , GFS (Global Finance Solution)

About the Organization: Amazon is a US-based multinational electronic commerce company headquartered in Seattle, Washington. Amazon.com started as an online bookstore, but soon diversified into many other categories, with a vision to be earth's most customer-centric company & to build a place where people can come to find and discover anything they might want to buy online.

About the role: Amazon's Global Finance Services (GFS) team is a fast-paced, team-focused, dynamic environment and delivering great experiences for our customers is top priority. GFS is seeking a Business Intelligence Engineer to support our Amazon Music finance team.

As a Data Engineer, You will be working on building and maintaining complex data pipelines, assemble large and complex datasets to generate business insights and to enable data driven decision making and support the rapidly growing and dynamic business demand for data.

You will have an opportunity to collaborate and work with various teams of Business analysts, Managers, Business Intelligence, and Data Engineers to determine how best to design, implement and support solutions. You will be challenged and provided with tremendous growth opportunity in a customer facing, fast paced, agile environment.

Key job responsibilities
* Design, implement and support an analytical data platform solutions for data driven decisions and insights
* Design data schema and operate internal data warehouses & SQL/NOSQL database systems
* Work on different data model designs, architecture, implementation, discussions and optimizations
* Interface with other teams to extract, transform, and load data from a wide variety of data sources using AWS big data technologies like EMR, RedShift, Elastic Search etc.
* Work on different AWS technologies such as S3, RedShift, Lambda, Glue, etc.. and Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
* Work on data lake platform and different components in the data lake such as Hadoop, Amazon S3 etc.
* Work on SQL technologies on Hadoop such as Spark, Hive, Impala etc..
* Help continually improve ongoing analysis processes, optimizing or simplifying self-service support for customers
* Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
* Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
* Enjoy working closely with your peers in a group of talented engineers and gain knowledge.
* Be enthusiastic about building deep domain knowledge on various Amazon’s business domains.
* Own the development and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.

Basic Qualifications

- 1+ 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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Experience Level

Entry Level