Software Development Engineer - Amazon MSK
Come build the future of data streaming with the Amazon Managed Streaming for Kafka (MSK) team!
We are seeking builders for our Amazon MSK service, a fully managed service that makes it easy for customers to build and run applications that use Apache Kafka to process streaming data. We are looking for engineers who are enthusiastic about data streaming, and are as passionate about contributing to open source as they are about solving real customers' business needs, at AWS scale.
As a member of the Amazon MSK team, you will be making contributions to the entire stack - the APIs and the workflows that make up the MSK service, the core Kafka platform, and stand-alone tools that make it easier for Kafka community to operate Kafka better. Upstream compatibility is a core tenet of MSK. Your code changes to the Kafka platform will be released back to open source. As a member of an AWS service that builds on top of a popular open source technology, this is a unique opportunity to work on a team that straddles both worlds – open source and Amazon-internal software. You will design and build new features, make performance improvements, identify and investigate new technologies, prototype solutions, build scalable services, and test and review changes, to deliver an exceptional customer experience.
The ideal candidate has experience designing large-scale systems supporting millions of transactions per second, enjoys solving complex software problems, and possesses analytical, design and problem-solving skills. Ideally you have an in-depth understanding of streaming data technologies like Amazon Kinesis or Apache Kafka, and experience with open-source data processing frameworks like Apache Spark, Apache Flink, or Apache Storm. Your responsibilities will include collaborating with other engineers to build a large scale AWS service, and work with senior leaders to define your team's roadmap, including identifying design and code changes needed in the underlying open source platforms.
Inclusive Team Culture
Here at AWS, 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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design.
· Strong problem solving ability and object-oriented design skills.
· Experience making contributions to open source platforms.
· Experience building extremely high volume and highly scalable online services.
· Experience operating highly available services.
· Experience with distributed systems, consistent hashing, distributed locking, check-pointing, and load balancing.
· Working knowledge of Hadoop, MapReduce, Kafka, Kinesis, Spark or other Big Data processing platforms.
· Ability to excel in a fast-paced, startup-like environment.
· Experience mentoring other engineers.
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, visit https://www.amazon.jobs/en/disability/us