Associate Cloud Consultant, Data Anaiytics, Aws Professional Services, Private

3 days ago

Toronto, Canada Amazon Web Services Canada, Inc. - D46 Full time

Bachelor’s degree or higher in Computer Science, Engineering, Mathematics or a related field with a conferral date within May 2023 to May 2025
- 1+ years of hands-on experience of programming in languages such as Python, Ruby, Go, Swift, Java,.Net, C++, Node.js, or similar object-oriented language.

At Amazon Web Services (AWS), we’re hiring highly technical Data Analytics consultants to collaborate with our customers and partners on key engagements. Our consultants will develop and deliver proof-of-concept projects, technical workshops, and support implementation projects. These professional services engagements will focus on customer solutions such as Data and Analytics, Artificial Intelligence (AI) and GenerativeAI (GenAI), Machine Learning (ML), HPC and more.
You will join as part of the AWS Professional Services (ProServe) Associate to Consultant (A2C), which focuses on the accelerate career development of university graduates and early career professionals.
Our team members work with enterprise customers locally, regionally and domestically. As such, this role has up to 75% travel associated. While many of our customers engage ProServe virtually, there is always the potential that a customer might choose to include travel in their contract.
Key job responsibilities
In this role, you will work with our partners, customers and focus on our AWS offerings such Amazon Kinesis, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Athena, Amazon SageMaker, Amazon Bedrock, Amazon Q, and Amazon Lex. You will help our customers and partners to remove the constraints that prevent them from leveraging their data to develop business insights.
A day in the life
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 bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs.
You will also have the opportunity to create white papers, writing blogs, build demos and other reusable collateral that can be used by our customers. Most importantly, you will work closely with our Solution Architects, Data Scientists and Service Engineering teams.
About the team
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 16 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 harmony. 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. As such, this is a customer facing role in a hybrid delivery model. Project engagements include remote delivery methods and onsite engagement that will include travel to customer locations as needed.
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.
- 1+ years of experience of Data platform implementation
- Hands on experience with building data or machine learning pipeline
- Experience with one or more relevant tools (SQL, PostgreSQL, Data lake, DynamoDB, Hadoop)
- Current experience with hands-on implementation and performance tuning of Kinesis, Kafka, Spark or similar implementations
- Masters or PhD in Computer Science, Physics, Engineering or Math.
- Familiar with Machine learning concepts
- Hands on experience working on large-scale data science/data analytics projects
- Experience Implementing AWS services in a variety of distributed computing, enterprise environments.
- Experience with at least one of the modern distributed Machine Learning and Deep Learning frameworks such as TensorFlow, PyTorch, MxNet Caffe, and Keras.
- Experience building large-scale machine-learning infrastructure that have been successfully delivered to customers.
- Experience defining system architectures and exploring technical feasibility trade-offs.
- Experiences developing cloud software services and an understanding of design for scalability, perfo

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