We are seeking a go-to-market (GTM) specialist to own the enablement and sales acceleration strategy for AWS's Open Data for AI portfolio, specifically Project Avalanche (Apache Iceberg on AWS),
We are seeking a go-to-market (GTM) specialist to own the enablement and sales acceleration strategy for AWS's Open Data for AI portfolio, specifically Project Avalanche (Apache Iceberg on AWS),
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Visium combines strategy, frontier AI, and deep regulated-industry expertise to build and deploy AI-native systems that reinvent how businesses operate - unlocking the value of AI at scale. We're not
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Quick apply
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Ai Data Analytics information
See Renton, WA salary details
$27.69 - $34.87
10% of jobs
$34.87 - $42.06
6% of jobs
$42.06 - $49.24
7% of jobs
$50.07 is the 25th percentile. Wages below this are outliers.
$49.24 - $56.42
14% of jobs
The median wage is $60.17 / hr.
$56.42 - $63.60
24% of jobs
$68.59 is the 75th percentile. Wages above this are outliers.
$63.60 - $70.79
19% of jobs
$70.79 - $77.97
11% of jobs
$77.97 - $85.15
3% of jobs
$85.15 - $92.33
2% of jobs
$92.33 - $99.51
2% of jobs
$99.51 - $106.70
1% of jobs
$27
$61
$106
How much do ai data analytics jobs pay per hour?
What is AI data analytics?
What skills and qualifications are needed to thrive as an AI data analyst?
How does an AI data analytics professional typically collaborate with cross-functional teams within an organization?
What is the difference between Ai Data Analytics vs Data Scientist?
| Aspect | Ai Data Analytics | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's in Data Science, Computer Science, or related fields; certifications in AI and data analytics | Bachelor's or higher in Data Science, Statistics, Computer Science; advanced degrees preferred |
| Work Environment | Tech companies, finance, healthcare; focus on AI-driven data analysis | Research labs, tech firms, finance; focus on data modeling and insights |
| Employer & Industry Usage | Used in industries leveraging AI for predictive analytics and automation | Used across industries for data modeling, predictive analytics, and research |
Ai Data Analytics professionals focus on applying AI techniques to analyze data and develop automated solutions, while Data Scientists build models and interpret data to generate insights. Both roles require strong analytical skills and familiarity with data tools, but Ai Data Analytics emphasizes AI implementation, whereas Data Scientists focus on statistical modeling and research.
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Sr. Worldwide Specialist - AI, Data & AI GTM
Seattle, WA • On-site
Full-time
Posted 19 days ago
Key responsibilities
Design, manage, and optimize sales plays and programs related to the Open Data for AI portfolio, including setting goals, establishing timelines, and tracking performance metrics.
Develop and deliver enablement content and programs such as webinars, workshops, and events to educate and enable sales teams and external partners.
Collaborate with cross-functional teams to position open table formats as the data foundation for AI and report on program status and strategic recommendations to senior leadership.
Amazon rating
7.4
Based on 7,177 frontline employees who took The Breakroom Quiz
Job description
We are seeking a go-to-market (GTM) specialist to own the enablement and sales acceleration strategy for AWS's Open Data for AI portfolio, specifically Project Avalanche (Apache Iceberg on AWS), Amazon SageMaker Unified Studio (Context), This role sits within the Data Sales Acceleration Team in the AWS WWSO Data and AI Foundations organization and is responsible for accelerating how AWS sales and technical teams position, sell, and deliver open data formats as the foundation for AI workloads.
The ideal candidate will develop and execute GTM programs that help the field understand the customer journey from legacy data lakes to open table formats (Iceberg) and unified analytics environments (SageMaker Unified Studio), positioning these services as critical infrastructure for AI/ML workloads. You will own worldwide programs and time-bound initiatives that help AWS sellers create and progress sales opportunities, design and deliver enablement content, and collaborate with Product Marketing, SA teams, and partner organizations to scale the Avalanche motion globally.
The ideal candidate will possess a proven track record in program management, business development, or pre-sales functions with domain knowledge of data lakes, open table formats, analytics, and agentic AI. They should have a demonstrated ability to think strategically and analytically about business, product, and technical challenges, with the ability to build and convey compelling value propositions, and work cross-organizationally to build consensus
This candidate must communicate clearly through Amazon business narratives, weekly status updates, and data-driven reporting using Quick to unlock business insights for leaders.
Key job responsibilities
Design, manage, and optimize sales plays and programs: set goals, establish timelines, develop RACI matrices, manage campaign codes and SFDC service mappings, and continuously track pipeline influence, win rates, and deal velocity to inform iteration
Own Sales play execution for the Open Data for AI portfolio (Project Avalanche/Iceberg, SageMaker Unified Studio, Context): define plays in Alchemy, create HighSpot pages with value propositions and discovery questions, publish to Sales Velocity Dashboard with complete metadata, push to Autonomous Prospecting, and track performance (Created ARR, win rate, deal velocity, launched ARR) across all AWS geographies
Develop and deliver internal and external enablement (virtual webinars, in-person roadshows, hands-on workshops, regional customer events via BOOST): analyze revenue and sentiment metrics to prioritize topics, build propensity-based target lists, execute multi-channel promotion, track 30-day (internal) and 6-month (external) pipeline influence via Zoom-to-SFDC matching, and feed the prescriptive scorecard
Collaborate with Avalanche GTM, SA organizations, and field specialists to position open table formats (Iceberg) as the data foundation for AI, disseminate competitive differentiation and customer proof points for the portfolio to field sellers and the AWS Partner Network
Report program status and strategic recommendations to senior leadership through Amazon business narratives and MBR documents, including pipeline metrics, scorecard verdicts, and resource allocation guidance
Design and deploy AI-powered productivity tools (Amazon Quick Desktop skills, Q Apps, Q Agents) to automate operational workflows across the team
A day in the life
The mission of the Data Sales Acceleration Team is to create and leverage mechanisms that increase the velocity of data and analytics sales from top-of-funnel lead generation to launching and scaling customers' data and analytics productions. As the Open Data for AI GTM Specialist, you will spend your time designing enablement programs that teach sellers to position Iceberg migrations, collaborating with the Avalanche GTM specialists' team on new launches, analyzing pipeline and attach metrics to identify coverage gaps, and running global enablement sessions. You will work across time zones with AWS employees from sales, solutions architecture, product marketing, and partner organizations.
About the team
The Data Sales Acceleration team drives GTM enablement and sales play execution for Database, Analytics, and Data Foundations for AI across seven workstreams: Program Management, Sales Play Execution, Internal Enablement, External Enablement, Content/HighSpot Management, Newsletters & Comms, and Productivity & AI Agents
Operating through a domain-mapped model integrated with Banjot Chanana's Data organization, the team builds scalable mechanisms the worldwide field self-serves, measures impact through closed-loop pipeline attribution, and prioritizes what to enable next based on revenue and sentiment signals.
About Amazon
Sourced by ZipRecruiter
Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.
Industry
It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development
Company size
10,000+ Employees
Headquarters location
Seattle, WA, US