Data Engineer, AVS

Amazon is a place where data drives most of our decision-making. Alexa Voice Services team is looking for a dynamic data engineer who can be innovative, strong problem solver and can lead the implementation of the analytical data infrastructure that will guide the decision making. As a Data Engineer, you think like an entrepreneur, constantly innovating and driving positive change, but more importantly, you consistently deliver mind-boggling results. You're a leader, who uses both quantitative and qualitative methods to get things done. And on top of it all, you're someone who wonders "What if?" and then seeks out the solution. This position offers exceptional opportunities to grow their technical and non-technical skills. You have the opportunity to really make a difference to our business by inventing, enhancing and building world class systems, delivering results, working on exciting and challenging projects.

A day in the life
Design, implement and support an analytical data infrastructure
Managing AWS resources including EC2, EMR, S3, Glue, Redshift, etc.
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies
Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis
Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
Maintain internal reporting platforms/tools including troubleshooting and development. Interact with internal users to establish and clarify requirements in order to develop report specifications.
Work with Engineering partners to help shape and implement the development of BI infrastructure including Data Warehousing, reporting and analytics platforms.
Contribute to the development of the BI tools, skills, culture and impact.
Write advanced SQL queries and Python code to develop solutions.

About the hiring group
As a Data Engineer, you are responsible for analyzing large amounts of business data, solve real world problems, and develop metrics and business cases that will enable us to continually delight our customers worldwide. This is done by leveraging data from various platforms such as Jira, Portal, Salesforce. You will work with a team of Product Managers, Data Scientists and Business Intelligence Engineers to automate and scale the analysis, and to make the data more actionable to manage business at scale. You will own many large datasets, implement new data pipelines that feed into or from critical data systems at Amazon.

Job responsibilities

Amazon is a place where data drives most of our decision-making. Alexa Everywhere team is looking for a dynamic data engineer who can be innovative, strong problem solver and can lead the implementation of the analytical data infrastructure that will guide the decision making. As a Data Engineer, you think like an entrepreneur, constantly innovating and driving positive change, but more importantly, you consistently deliver mind-boggling results. You're a leader, who uses both quantitative and qualitative methods to get things done. And on top of it all, you're someone who wonders "What if?" and then seeks out the solution. This position offers exceptional opportunities to grow their technical and non-technical skills. You have the opportunity to really make a difference to our business by inventing, enhancing and building world class systems, delivering results, working on exciting and challenging projects.


As a Data Engineer, you are responsible for analyzing large amounts of business data, solve real world problems, and develop metrics and business cases that will enable us to continually delight our customers worldwide. This is done by leveraging data from various platforms such as Jira, Portal, Salesforce. You will work with a team of Product Managers, Data Scientists and Business Intelligence Engineers to automate and scale the analysis, and to make the data more actionable to manage business at scale. You will own many large datasets, implement new data pipelines that feed into or from critical data systems at Amazon.

You must be able to prioritize and work well in an environment with competing demands. Successful candidates will bring strong technical abilities combined with a passion for delivering results for customers, internal and external. This role requires a high degree of ownership and a drive to solve some of the most challenging data and analytic problems in retail. Candidates must have demonstrated ability to manage large-scale data modeling projects, identify requirements and tools, build data warehousing solutions that are explainable and scalable. In addition to the technical skills, a successful candidate will possess strong written and verbal communication skills and a high intellectual curiosity with ability to learn new concepts/frameworks and technology rapidly as changes arise.

Responsibilities
· Design, implement and support an analytical data infrastructure
· Managing AWS resources including EC2, EMR, S3, Glue, Redshift, etc.
· Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies
· Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
· Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis
· Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
· Maintain internal reporting platforms/tools including troubleshooting and development. Interact with internal users to establish and clarify requirements in order to develop report specifications.
· Work with Engineering partners to help shape and implement the development of BI infrastructure including Data Warehousing, reporting and analytics platforms.
· Contribute to the development of the BI tools, skills, culture and impact.
· Write advanced SQL queries and Python code to develop solutions.



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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Basic Qualifications

· 3+ 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
· Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline
· 4+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets
· Experience using big data technologies (Hadoop, Hive, Hbase, Spark, EMR, etc.)
· Knowledge of data management fundamentals and data storage principles
· Knowledge of distributed systems as it pertains to data storage and computing

Preferred Qualifications

· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
· Coding proficiency in at least one modern programming language (Python, Ruby, Java, etc)
· Implement standardized, automated operational processes to deliver accurate and timely data for reporting to meet or exceed SLAs
· Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
· Experience transforming complex data sets. Experience in evaluating data accuracy and quality.
· Experience working directly with remote technical teams and client services
· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
· Implement standardized, automated operational processes to deliver accurate and timely data for reporting to meet or exceed SLAs
· Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
· Experience providing technical leadership and mentoring other Data Engineers for best practices on data engineering