Senior Software Dev Engineer, MWAA-Serverless

Translate functional and technical requirements into detailed architecture, design and extensible code

• Technically lead a team of smart engineers on complex projects

• Be an advocate of industry best-practices to produce reliable, fault-torrent and dependable code

• Code and test complex system modules; develop and leverage frameworks to be effective and efficient

• Participate in architecture, design and code reviews to maintain our high development standards

• Own system architecture, scalability, reliability, and performance

• Collaborate and influence other teams to deliver and operate large scale, distributed services in the cloud

• Mentor other engineers, defining our challenging technical culture, and helping to build a fast-growing team

Passionate in building large scale distributed systems

• Thrive in culture of ownership, delivery and bias for action

• Fast pace environment energizes you to be at your best

• Innovate and invent in agile and collaborative environment

• Curious and eager to learn to expect more of you and others, 5+ years of non-internship professional software development experience

• 5+ years of programming with at least one software programming language experience

• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience

• Experience as a mentor, tech lead or leading an engineering team

Preferred Qualifications

• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

• Bachelor’s degree in computer science or equivalent

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

AWS Data Processing and Experience group provides rapidly growing, industry acclaimed cloud services in areas of big data platforms to data analytics to operational databases. The group is at the forefront of innovation in these areas producing world-class cloud services such as MWAA, Glue, EMR, Athena and many more.

The Team:

Amazon MWAA serverless is a serverless service for Apache Airflow that lets you use your current, familiar Apache Airflow platform to orchestrate your workflows. You gain improved scalability, availability, and security without the operational burden of managing underlying infrastructure.

Top reasons to join our team:

• Be part of big data revolution in cloud

• Be catalyst to deliver a truly disruptive product(s) that are growing rapidly

• Learn how to build & operate distributed systems at massive scale

• Solve unique and first-order problems in areas of Big Data, serverless computing, Spark, Distributed Systems and Machine Learning

• You get to define, build, own, and run a service in high growth environment

• Influence and build products that will leverage scale of resources to run serverless big data workloads