Data Engineer Amazon
Boston, MA

Job Description

Do you want to build the analytics to understand and accelerate large scale migrations to AWS? Migrating to AWS is one of the most impactful business decisions AWS customers make and we want your help to better understand our customers' migration journeys. For customers large and small, migrating to AWS can have an enormously positive impact on their costs, agility, and employee growth. Here in the Migration Services team, we're working closely with customers to invent new approaches to migrations, build scalable systems, and use machine learning to solve problems that haven't been solved yet.

As a Data Engineer in AWS Migration Services you will work on the data pipeline and analytics to provide business and engineering stakeholders key insights into our customers' migration journeys. You will get the exciting opportunity to interact with very large data sets in one of the most complex data warehouse environments. Our data pipeline combines metrics from multiple data sources including Amazon Redshift, Salesforce, and Amazon S3. You will have the opportunity to help business and engineering stakeholders determine what migration related metrics they should be tracking and establish new and expand existing automated data collection to feed into the data pipeline. You will regularly apply your analytical and problem solving skills and perform analysis with tools like Jupyter, SageMaker, and Pandas so we better understand customer migrations and how we can accelerate their migrations.

Day-to-day you will:

* Work closely with product management, sales, and business stakeholders to analyze data from a multitude of sources about customers' migrations and how we can accelerate their migrations.
* Design, implement, and maintain a data pipeline and analytical environment using third-party and in-house reporting tools, modeling metadata, and building reports and dashboards.
* Use creative problem-solving to automate the collection and analysis from available data sources in order to deliver actionable output.
* Iteratively improve analysis and identify new metrics to improve analytics.