Sr Streaming Data Engineer

San Francisco, California, USA

Full Time Senior-level / Expert USD 76K - 150K *
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Job summary
Are you a streaming systems specialist? Do you have real-time systems experience? Do you like to solve the most complex and high scale (billions + records) data challenges in the world today? Would you like a career that gives you opportunities to help customers and partners use cloud computing to do big new things faster and at lower cost? Do you want to be part of history and transform businesses through cloud computing adoption? Do you like to work in a variety of business environments, leading teams through high impact projects that use the newest data analytic technologies? Would you like a career path that enables you to progress with the rapid adoption of cloud computing?

At Amazon Web Services (AWS), we’re hiring highly technical streaming data engineers to collaborate with our customers and partners on key engagements. Our consultants develop and deliver proof-of-concepts, technical workshops, deliver implementation projects and create solutions and tools. These professional services engagements involve emerging technologies like AI, IoT, and Data Analytics.

The focus of this role is leading and helping our customers and partners with design, implementation and integration of solutions using Amazon managed streaming services. AWS Professional Services engage in a wide variety of projects for customers and partners, providing collective experience from across the AWS customer base and are obsessed about customer success. Our team collaborates across the entire AWS organization to get the right solution delivered and drive feature innovation based upon customer needs.

• Expertise - Collaborate with AWS field sales, pre-sales, training and support teams to help partners and customers learn and use AWS services such as Amazon MSK, Kinesis (KDS, KDF, KDA), Glue, EMR and more.

• Solution - Deliver on-site technical engagements with partners and customers. This includes participating in pre-sales on-site visits, understanding customer requirements, supporting consulting proposals, contributing to internal Area of Depth programs and Technical Field Community, authoring AWS Data Analytics best practice and creating packaged data service offerings.

• Delivery - Engagements include on-site projects to architect, design and build customer’s data streaming implementations and helping customers to migrate existing self-managed and on-premises solutions to AWS.

• Ability to travel to client locations to deliver professional services, as needed.

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 85,000 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.
Work/Life Balance
Our team puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here. We are a customer-obsessed organization—leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust.
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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

Basic Qualifications


qualifications
• Bachelor’s degree, or equivalent experience, in Computer Science, Engineering, Mathematics or a related field
• 5+ years’ industry experience as a Data Engineer with demonstrated experience in data modeling, ETL Development, Data Warehousing, Data Lakes, and/or consoliding data from distributed systems
• 2+ years’ experience building enterprise level streaming and real-time architecture
• Experience with implementation, integration and administration with at least one of the following Streaming Data-Streaming frameworks or services: Apache Kafka, Kinesis Data Streams, Apache Spark Streaming, Apache Flink, Apache Storm, Apache NiFi, Azure Stream Analytics, or Confluent.

Preferred Qualifications

• Masters in Computer Science, Physics, Engineering or Math
• AWS Associate level certifications
• Industry leadership in the fields of streaming and real-time processing
• Ability to think strategically about business, product, and technical challenges in an enterprise environment
• Ability to earn customer trust and influence decision making at the strategic (CxO, VP) and the technical (Architect, Engineer) level
• Experience driving discussions with senior personnel regarding trade-offs, best practices, project management and risk mitigation
• Experience developing innovative solutions to complex business and technology problems
• Experience in queuing theory with message-broker software like RabbitMQ or similar



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.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

* Salary range is an estimate based on our salary survey at salaries.ai-jobs.net
Job region: North America
Job country: United States
Job stats:  1  0  0
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