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Sr. Specialist Solution Architect - Data Analytics, Data & AI Specialist Solutions Architect team

Sr. Specialist Solution Architect - Data Analytics, Data & AI Specialist Solutions Architect team
Sydney, NSW, AUS
·
On-site
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Full-time
·
1mo ago
필수 스킬
AWS
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AWS Specialist Solutions Architects (SSAs) are technologists with deep domain-specific expertise, able to address advanced concepts and feature designs. As part of the AWS sales organization, SSAs work with customers who have complex challenges that require expert-level knowledge to solve. SSAs craft scalable, flexible, and resilient technical architectures that address those challenges. This might involve guiding customers as they refactor an application or designing entirely new cloud-based systems. Specialist SAs play a critical role in capturing customer feedback, advocating for roadmap enhancements, and anticipating customer requirements as they work backwards from their needs. As domain experts, SSAs also participate in field engagement and enablement, producing content such as blogs and workshops for customers, partners, and the AWS Technical Field.
Data analytics SSAs combine technical skills in data, analytics, AIML with business acumen, and technical sales skills. They are focused on supporting customers throughout the engagement lifecycle and work closely with the teams that support implementation including AWS Professional Services and Partners. SSAs unblock customers and help them get to production faster. Joining AWS as a Specialist Solutions Architect will give you opportunities to work on interesting and challenging problems, collaborate with a group of skilled practitioners focused on delivering outcomes for our customers, and be part of a diverse and inclusive community committed to being Earth’s Best Employer.
Specialist Solutions Architects are part of the Amazon Global Sales Organization (AGS) which builds and executes go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. Our teams include business development, specialist sales, and specialist solutions architecture, working together to provide customer-obsessed solutions that help people run their businesses more effectively. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #One Team
Key job responsibilities
Design best in class data analytics solutions for all stages of customer and product lifecycles.
Partner with SAs, Sales, Business Development and Service teams to accelerate customer adoption and revenue attainment.
- Thought Leadership
- Evangelize and share best practices through forums such as AWS blogs, reference architectures and public-speaking events such as AWS Summit, AWS re: Invent, etc.
Act as a technical liaison between customers and the AWS teams to provide customer driven product improvement feedback.
Develop and support an AWS internal community of related subject matter experts.
A day in the life
Watch this video to find out what it’s like to be a Solutions Architect at AWS?
About the team
This role is part of the Data and AI specialist team for Australia and New Zealand. As a member of this team you will work with customers and be based out of our Auckland offices. You will focus on customers across New Zealand, working directly with customers across industry verticals, from large Enterprises to start-ups, across all stages of their cloud journey.
Basic Qualifications
- 10+ years of design, implementation, or consulting in applications and infrastructures experience
- 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 7+ years of implementation and architecture experience in big data, data warehousing, data lake, operational analytics, data migration, and integration scenarios. (e.g. Amazon EMR, Hadoop, Spark, R, Presto, Hive, Amazon Redshift, Teradata, Vertica, Glue, Data Migration Services)
Preferred Qualifications
- 5+ years of infrastructure architecture, database architecture and networking experience
- 3+ years of implementation and architecture experience in ml ops, model hosting, model validation, data processing. (Amazon Sage Maker, Amazon Bedrock, Kubeflow, MLflow)
- Knowledge of data and AI services and solutions (e.g. data lakes, data warehouses, big data, search, streaming, machine learning and GenAI) and their architecture and infrastructure needs
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, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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Amazon 소개

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
직원 수
Seattle
본사 위치
$1.5T
기업 가치
리뷰
2.9
10개 리뷰
워라밸
2.8
보상
3.7
문화
2.5
커리어
2.3
경영진
2.1
35%
친구에게 추천
장점
Good pay and compensation
Strong benefits package
Flexible scheduling options
단점
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
연봉 정보
4개 데이터
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0개 리포트
$108,330
총 연봉
기본급
$43,332
주식
$54,165
보너스
$10,833
$75,831
$140,829
면접 경험
10개 면접
난이도
3.7
/ 5
소요 기간
21-35주
합격률
20%
경험
긍정 10%
보통 10%
부정 80%
면접 과정
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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