Cloud Architect: Data Analytics

Overview
Cloud Architect: Data Analytics & GenAI, AWS Professional Services
Job ID: 3070458 | Amazon Web Services Australia Pty Ltd
AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments.
Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services.
Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center.
You'll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
Are you a Cloud Architect with GenAI experience?
Do you have real-time Data Analytics, Data Warehousing, Big Data, Modern Data Strategy, Data Lake and Data Engineering experience?
Do you like to solve the most complex and high scale (billions+ records) data challenges?
Do you like leading teams through high impact projects that use the latest data analytics technologies?
Would you like a career path that enables you to progress with the rapid adoption of cloud computing?
AWS Professional Services are hiring a highly technical Cloud Architect specialised in Data Analytics and GenAI to collaborate with our customers and partners to derive business value from the latest Data Analytics and GenAI services.
Our consultants will develop and deliver proof-of-concept projects, technical workshops and support complex projects.
These professional services engagements will focus on customer solutions such as batch, real-time data capture and analysis, driving data driven decisions and desired customer outcomes.
Responsibilities
Expertise: Collaborate with pre-sales and delivery teams to help partners and customers learn and use services such as AWS Glue, Amazon S3, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, Amazon Redshift, Amazon Athena, AWS Lake Formation, Amazon DataZone, Amazon SageMaker, Amazon Quicksight and Amazon Bedrock.
Solutions: Deliver technical engagements with partners and customers, including participating in pre-sales visits, understanding customer requirements, creating consulting proposals and packaged data analytics service offerings.
Delivery: Lead engagements that demonstrate how AWS services support new distributed computing solutions, often spanning private and public clouds; migrate and modernise existing data applications and develop new data applications using AWS services.
Innovation: Work with customers and partners to apply Artificial Intelligence to business challenges, designing experiments and exploring new algorithms to optimize risk, profitability, and customer experience using Data Analytics and GenAI.
Hands-on: Use ML and Generative AI tools (e.g., Amazon SageMaker, Amazon Bedrock) to provide scalable cloud environments for data labeling, model building, training, tuning, and deployment.
Day-to-day and Team
A day in the life: AWS Professional Services (ProServe) is a global team helping enterprise customers achieve business outcomes on AWS Cloud.
ProServe consultants work with many of the world's largest enterprises to deliver cloud initiatives.
About the team: AWS values diverse experiences and encourages candidates to apply even if they do not meet every preferred qualification.
If your career is just starting or non-traditional, apply anyway.
BASIC QUALIFICATIONS
5+ years of IT implementation experience
Experience facilitating discussions with senior leadership regarding technical/architectural trade-offs, best practices, and risk mitigation
Experience and technical expertise in cloud computing technologies
Experience implementing AWS and/or third-party Data Analytics services (e.g., Amazon Redshift, AWS Glue, AWS Lake Formation, dbt, Spark, Python); programming in Python, R, Matlab, Java or other modern languages
Ability to work with customers to define requirements and translate them into practical data analytics solutions
PREFERRED QUALIFICATIONS
Strategic thinking about business, product, and technical challenges in an enterprise environment
Hands-on experience leading large-scale global data analytics projects aligned with business use cases
Experience in Data Quality management: processes to measure and manage data quality, enforce data controls, and provide data assurance
Experience implementing AWS services in diverse distributed computing and enterprise environments
Customer-facing skills to represent AWS within the customer environment and drive discussions with senior personnel regarding trade-offs, best practices, project management and risk mitigation
Acknowledgement of country: In the spirit of reconciliation Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community.
We pay our respect to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
IDE statement: Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit the accommodations page for more information.
If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
#J-18808-Ljbffr