Data Engineering Manager, AmazonPay DIAS

Job summary
What is Amazon Pay?

Amazon Pay is a high growth startup business within Amazon. Started in 2015, Amazon Pay is now available in 18 countries, allowing buyers to leverage Amazon’s trusted, convenient, and rewarding wallet for 3rd party purchase experiences online, in-store, and with Alexa.


Key job responsibilities
As a Data Engineering Manager you will partner closely with SDEs, Data Scientists, Product Managers and Business Intelligence Engineers to define and deliver world-class data solutions and products. You will be responsible for evolving our long-term roadmap of projects, defining tech stack & operational strategies. As a Data Engineering Manager, you will lead a team of data engineers, provide technical leadership, drive data engineering initiatives and build end-to-end data solutions that are highly available, scalable, stable, secure, and cost-effective. You strive for simplicity, demonstrate creativity and sound judgement. You deliver data solutions that are customer focused, easy to consume and create business impact. You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics. You have a strategic and long term view on architecting advanced data eco systems. You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.

Responsibilities

• Lead a team of Data Engineers to deliver cross-functional, data engineering projects
• Establish and clearly communicate organizational vision, goals and success measures.
• Collaborate with global business and tech stakeholders to develop roadmap and product requirements.
• Build, Own, Prioritize, Lead and Deliver a roadmap of large and complex multi-functional projects and programs.
• Manage AWS resources such as EC2, RDS, Redshift, Kinesis, EMR, Lambda etc.
• Collaborate with BIEs and Scientists to deliver high quality data architecture and pipelines.
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
• Own the design, development, and maintenance of metrics, reports, analyses, dashboards, etc. to drive key business decisions.

About the team
Mentorship and Career Growth
Our team is dedicated to supporting new team members. Our team has a broad mix of experience levels and Amazon tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We enjoy on-boarding new team members through one-on-ones, buddy programs, and regular mentorship.

Work/Life Balance
Our team is focused on balancing life with work, and does this via work autonomy and by prioritizing solutions and processes that enable us to scale faster than the business. We recognize that setting schedules for being in-office and working from home are personal choices, and support every employee in setting a schedule that works for them.

Inclusive Team Culture
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Basic Qualifications

• 3+ Years managing and scaling a high performing Data Engineering (or similar) team.
• 5+ Years with hands on exposure to data modeling, data warehousing, and building ETL pipelines at scale.
• 5+ years industry experience
• Degree in Computer Science, Engineering, Mathematics, or a related field
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience leading and influencing the data strategy of your team or organization.
• Eagerness to be a player-coach and lead by example.

Preferred Qualifications

• 3-5+ years of people management experience, managing engineers
• 3-5+ years of relevant engineering experience
• Experience building data products incrementally and integrating and managing datasets from multiple sources
• Experience with common technologies and tools including but not limited to (Redshift, EMR, Spark, Python, SQL)
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations



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.