Data Engineer, Amazon Devices-Demand Planning

- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with SQL
- 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)
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.

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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.
The Amazon Devices-Demand Planning team is seeking an outstanding Data Engineer with solid analytical thinking, metrics driven decision making and problem-solving skills. As a Data Engineer, you design, build and enhance data management solutions supporting our demand forecasting models and reporting tools using Big Data tools and AWS technologies like Redshift, S3, Glue, SNS, Lambda. The ideal candidate relishes working with large volumes of data, enjoys the challenge of highly complex ambiguous contexts, and, above all else, is passionate about data and analytics. An expert with data modeling, ETL design and data warehousing solutions and passionately partners with the business to deliver high quality data architecture and pipelines. The ideal candidate has excellent communication skills and ability to work effectively with our customers and stakeholders including Data Scientists, Software Engineers and BI Engineers. The ideal candidate will be a leader, quick learner and be able to work independently. He/she should be able to operate in a very fast paced environment to support the rapidly growing and dynamic business demand for data, and use it to deliver data as service which will have an immediate influence in day-to-day business decision making.

Key job responsibilities
• Design and implement scalable extract, transform, and load (ETL) processes.
• Manage and maintain large datasets, production pipelines and jobs that that feed into or from critical demand forecasting models and reporting.
• Work closely with senior engineers to drive data architecture for Devices Demand Planning.
• Collaborate with product managers, data scientists and engineers to continually improve ongoing processes and to develop and improve the current data architecture, data quality, and data availability.
• Manage and execute against project plans and delivery commitments.
• Manage data infrastructure including AWS resources like S3, Redshift, Glue, etc.
• Make recommendations to improve performance and/scalability either through updates based on a technical need or through innovation.


About the team
Data Engineering team within Demand Planning supports Data Infrastructure, Data Architecture and Data Management functions. This includes sourcing, ingesting, and processing of large datasets; building and optimizing logical and physical data models; curation of Input data for forecasting models, publishing data, and enhancing data management solutions supporting Demand Forecasting models and reporting tools.