Manager, Data Engineering

DESCRIPTION
Are you a driven engineering leader who wants to have a direct impact on customers and the team? Help us improve the customer experience for Consumer Payments!

About the Role
The Payment Acceptance & Experience (PAE) team is a Manager for our Data Engineering team. The PAE team, within Consumer Payments organization, has the mission to build the most trusted, intuitive, and accessible payment experience on Earth. As the Data Engineering Manager, you will lead a team of Data Engineering professionals to build scalable data infrastructure, data pipelines, and innovations. You will partner with Business Intelligence, Data Science, and Product Management teams to enable the creation of data-driven business insights, machine learning models, and innovative solutions.
We are looking for a leader that is passionate about using data to improve the customer paying experience and business decision making process. In this role you will work across payments teams including marketing, brand, design, and software engineering to align on the Data Engineering roadmap. You will lead a team to solve complex design, scaling, and storage problems, looking around corners to continuously raise the bar on our data capabilities to meet the current and future needs of the business. You will continually coach, develop, and mentor your team to achieve strong levels of performance and their personal development goals.

Day-to-Day Expectations
· Inspire and manage a talented Data Engineering team to achieve its goals and development potential
· Define and manage a long-term vision and portfolio of initiatives to improve the customer experience and business results through creating world-class data infrastructure and enabling data-driven science solutions, including algorithms and models integrated in production systems
· Drive a Data Engineering roadmap; prioritize engineering requests to balance the tactical and strategic information needs of the business
· Ability to design data systems that can scale to the billions of payment transactions and invent mechanisms to enable business insights
· Collaborate and partner with PAE organization to understand, anticipate, and respond to current and future needs
· Connect with the Amazon community of data professionals to stay current on technology trends, data tools and techniques to improve the performance of the team
· Create and foster an environment that values and promotes an inclusive approach to problem solving and continuous learning to improve

· Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, 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

· Experience managing Data Engineers, Software Engineers, and/or Business Intelligence Engineers
· Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline
· 5+ years of industry experience in Data Engineering, Software Development, Business Intelligence, Data Science, or related field with a track record of manipulating, processing, and extracting value from large datasets
· Hands-on experience and advanced knowledge of SQL
· Experience in data modeling, ETL development, and data warehousing
· Experience using big data technologies (Hadoop, Hive, Hbase, Spark, EMR, etc.)
· Knowledge of data management fundamentals and data storage principles
· Proficiency in at least one modern programming language such as Python, Perl, Ruby, or Java

Preferred Qualifications

· Experience working with AWS big data technologies (Redshift, S3, EMR)
· Experience building complex data systems that handle large data sets and that have been successfully delivered to customers
· Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
· Ability to lead a team to deliver a project/program from scoping requirements through actual launch
· Experience in communicating with users, other technical teams, and management to collect requirements, explain data infrastructure choices, and describe data engineering strategy