At Amazon, we’re working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and visionary people. AWS Demand Planning is seeking a Data Engineer with a combination of superior analytical abilities, business acumen, business judgement, curiosity, technical skills, and written and verbal communication skills to join our team.
Data-driven decision-making is at the core of Amazon’s culture and people who are exceptionally talented at building data infrastructures to support reporting and analytics needs of the business are critical. Your work will directly impact the decisions and strategy of the entire AWS Demand Planning team and our customers. As an Amazon Data Engineer, you will be working in one of the world’s largest data warehouse environments. This environment processes millions of time series events each week to build and test models for generating forecasts for all AWS services. These models and forecasts will be used in business reporting solutions that are consumed by thousands of users worldwide to optimize service availability and infrastructure costs. Your data solutions will be supporting the growth of one of the world’s largest Cloud.
An ideal candidate will have excellent communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. You should be able to demonstrate an expertise in designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing applications. You should be able to work with business customers in a fast-paced environment by understanding their business requirements and implementing reporting solutions. You will also gain an understanding of Supply Chain Management for the Cloud and develop a deep understanding of the internal workings of all AWS Services. Your role will leverage AWS technologies such as Lambda, Glue, and Kinesis to craft data solutions. The successful candidate will not only possess the expertise and passion for data, and build tools to solve for business challenges, but also will interact directly with business leaders and teams to answer important business questions and drive change.
The data engineer must be a self-starter, comfortable with ambiguity, able to think big and be creative (while still paying careful attention to detail), and enjoy working in a fast-paced, dynamic environment. If you are excited about data and results-oriented, and want to join a growing analytics team within Amazon – this role is for you!
The primary responsibilities of this role include:
· Working with managers, software developers, BI engineer and scientists to design and develop data infrastructure to support the growth of AWS.
· Enabling effective decision making by retrieving and aggregating data from multiple sources and compiling it into digestible and actionable forms.
· Performing deep-dives to find root causes of variances in data between different sources.
· Writing high quality SQL to create and store large data sets.
· Developing a deep understanding of our vast data sources and identify which to use to solve specific business problems.
· Optimizing the performance of business-critical queries and dealing with ETL job related issues.
· Tuning application and query performance using SQL.
· Identifying the data quality issues across the various platforms at Amazon.
· Bachelor’s degree in Engineering, Statistics, Computer Science, or a related quantitative field
· 1+ years of experience in a data engineering position or similar
· Experience with SQL, data warehousing and OLAP technologies
· Design and scripting experience in Python, Java, etc.
· Master’s degree or higher in Engineering, Statistics, Computer Science, or an equivalent quantitative field
· 3+ years of experience working as a data engineer in a business environment
· Experience with AWS services like S3, Redshift, Athena, RDS, Lambda etc.
· Experience communicating results and business impact of analytical deep dives to senior leadership
· Experience working in a technology company
· Experience with BI data visualization and delivery tools such as Power BI, Tableau, Qlik, Quicksight, etc.
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