Sr. Worldwide GTM Specialist - DynamoDB, Data & AI GTM
WS DynamoDB GTM is seeking a Senior Worldwide GTM Specialist to accelerate adoption of Amazon DynamoDB as the backbone of modern, high-scale application architectures. This role drives strategic GTM initiatives positioning DynamoDB as the default choice for operational workloads requiring single-digit millisecond latency, infinite scalability, and zero operational overhead — from internet-scale applications to agentic AI data layers.
Technical Focus:
DynamoDB architecture: single-digit millisecond reads/writes at any scale, on-demand vs. provisioned capacity modes, global tables for multi-region active-active deployments
Data modeling patterns: single-table design, adjacency lists, composite sort keys, GSI overloading, and sparse indexes for complex access patterns
Migration pathways: relational-to-DynamoDB modernization (Oracle/SQL Server/MySQL → DynamoDB), dual-write patterns, CDC-based migration using DMS, and DynamoDB Import for bulk data loading
Integration with AI/ML workloads: DynamoDB as session state, vector metadata store, and tool-use data layer for agentic AI architectures (MCP, NL2SQL gateway patterns)
Zero-ETL and streaming: DynamoDB Streams, Kinesis Data Streams integration, export to S3 for analytics, and zero-ETL to Redshift/OpenSearch
Operational excellence: DAX (in-memory caching), TTL-based data lifecycle management, point-in-time recovery, and cost optimization strategies
GTM Characteristics:
Strategic scope: Worldwide motion — define and scale repeatable DynamoDB engagement patterns across geos, segments (ENT, STRAT, SMB), and verticals
Migration-first pipeline: Owns the GTM motion for relational-to-DynamoDB modernization — the highest-ARR pipeline driver for the service
Cross-functional execution: Bridges DynamoDB product/engineering, field specialists, SAs, and account teams to align on unified positioning against competitors (MongoDB Atlas, GCP Firestore/Bigtable, Azure Cosmos DB)
Field enablement: Builds scalable programs — sales plays, migration assessment tools, battle cards, proof points, and field motions that convert discovery into pipeline
Customer engagement: Comfortable in deep technical discovery with architects and engineering leaders; can whiteboard single-table designs, discuss partition key strategies, and articulate why DynamoDB eliminates operational overhead vs. self-managed NoSQL
Pipeline & adoption metrics: Directly accountable for DynamoDB new workload adoption, migration pipeline growth, and cross-service attach (DynamoDB → Streams → analytics)
Competitive positioning: Technical fluency to counter MongoDB ("developer familiarity"), Cosmos DB ("multi-model"), and Firestore ("serverless simplicity") with trust-based differentiation rooted in DynamoDB's operational track record at scale
Data and AI GTM — Senior Worldwide GTM Specialist
Job Summary: The AWS Data and AI GTM team is seeking a Senior Worldwide GTM Specialist to drive cross-service go-to-market strategies that connect AWS's data platform (databases, analytics, storage) with AI/ML workloads — particularly agentic AI, generative AI, and foundation model integration patterns. This role sells across service boundaries, positioning the full AWS data platform as the differentiated foundation for AI-ready enterprises.
Technical Focus:
Data foundations for AI: how databases (Aurora, DynamoDB, Neptune, OpenSearch) and analytics (Redshift, Athena, Glue, EMR) enable retrieval-augmented generation (RAG), vector search, knowledge graphs, and agentic workflows
Agentic AI architecture patterns: MCP (Model Context Protocol), tool-use frameworks, NL2SQL, semantic layers, and AI-database integration
Data quality, governance, and lineage as prerequisites for trustworthy AI outputs
Reverse-attach motion: AI workloads (Bedrock, SageMaker) driving new data platform consumption
Cross-service value prop: zero-ETL pipelines, unified data access, and the platform advantage vs. single-service competitors (Snowflake, Databricks, GCP Spanner/AlloyDB, Azure Fabric)
GTM Characteristics:
Cross-service storytelling: Breaks down service team silos — articulates the unified AWS data platform advantage that no competitor can match at scale (1M+ customers trust AWS databases)
Play-based execution: Operates within structured sales plays (e.g., "Data Foundations for AI" — $653M+ Created ARR) and emerging plays (DAAP / Data and Agentic AI Accelerator Pathways)
Customer maturity model: Engages customers at different stages — from data modernization (crawl) to AI-ready architectures (run) — with stage-appropriate messaging
Competitive positioning: Technical fluency to counter GCP (AlloyDB/Spanner), Azure (Cosmos DB/Fabric), and Snowflake/Databricks with honest, trust-based differentiation
Metrics-driven: Tracks AI attach rates (DB→AI, AI→Data reverse attach), pipeline velocity, and cross-service consumption as success indicators
Field scalability: Builds enablement assets, working sessions, and prospecting day motions that help field teams sell the platform story independently
Key job responsibilities
Develop and execute GTM strategies that accelerate DynamoDB adoption for mission-critical operational workloads — including internet-scale applications, gaming backends, ad-tech platforms, and agentic AI data layers requiring single-digit millisecond latency at any scale.
Drive relational-to-DynamoDB modernization pipeline by defining migration GTM motions (Oracle/SQL Server/MySQL → DynamoDB), building assessment frameworks, and scaling engagement patterns that convert migration discovery into qualified pipeline across ENT, STRAT, and SMB segments.
Position DynamoDB as the default NoSQL choice against competitive alternatives (MongoDB Atlas, Azure Cosmos DB, GCP Firestore/Bigtable) through trust-based differentiation rooted in operational track record, scale economics, and zero-ops architecture.
Identify and scale repeatable customer engagement models — architectural GTM plays for single-table design adoption, global tables multi-region patterns, and DynamoDB-to-analytics integration (Streams, zero-ETL to Redshift/OpenSearch, S3 export) that drive cross-service attach and platform stickiness.
Build scalable field enablement programs including migration playbooks, data modeling workshops, competitive battle cards, proof-of-concept guides, and prospecting day content that equip field specialists and SAs to independently sell DynamoDB modernization.
Partner across AWS database, analytics, AI/ML, and partner organizations to define and operationalize DynamoDB's role in modern architectures — including integration patterns with Bedrock (agentic tool-use), Lambda (event-driven), and streaming services (Kinesis, EventBridge).
Analyze customer adoption trends, competitive dynamics, and market signals (including SIFT insights, PFR demand signals, and field feedback) to identify growth opportunities, influence product roadmap priorities, and refine GTM positioning globally.
Own worldwide metrics and reporting for DynamoDB GTM motions — tracking new workload adoption, migration pipeline velocity, cross-service consumption (DynamoDB → Streams → analytics), and competitive win/loss patterns to inform strategy iterations.
Data and AI GTM — Key Responsibilities
Develop and execute cross-service GTM strategies that position the full AWS data platform (databases, analytics, storage) as the differentiated foundation for AI/ML workloads — including RAG architectures, vector search, knowledge graphs, and agentic AI patterns.
Drive the "Data Foundations for AI" sales play and emerging motions (DAAP / Data and Agentic AI Accelerator Pathways) by defining customer engagement models that connect data modernization to AI readiness across maturity stages (crawl → walk → run).
Position AWS's cross-service platform advantage against unified-story competitors (Snowflake, Databricks, GCP AlloyDB/Spanner, Azure Fabric) — leading with customer trust and adoption scale rather than portfolio breadth, with honest gap acknowledgement where needed.
Identify and scale repeatable AI-attach engagement patterns — reverse-attach motions (Bedrock/SageMaker → new data consumption), NL2SQL gateway patterns, MCP-based agentic integrations, and semantic layer strategies that drive platform-wide ARR growth.
Build scalable field enablement and positioning for cross-service storytelling — sales plays, working sessions, architecture decision guides, and prospecting day motions that help field teams sell across service boundaries (not within silos).
Partner across AWS database, analytics, AI/ML, and storage teams to break down organizational boundaries and operationalize the platform story — aligning GTM messaging, joint customer engagements, and integrated pipeline motions that reflect how customers actually buy.
Analyze AI-attach rates, pipeline velocity, competitive dynamics, and SIFT field signals to identify growth opportunities, quantify the data-to-AI pipeline, and influence GTM priorities across the Data and AI organization.
Own worldwide metrics for Data and AI GTM motions — tracking DB→AI attach, AI→Data reverse attach, cross-service consumption, and play-level ARR (Created/Launched) to inform leadership decisions and strategy iterations.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.- 5+ years of Go-To-Market, Business Development, Sales, or Consulting experience
- 5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Experience developing strategies that influence leadership decisions at the organizational level
- Experience managing programs across cross functional teams, building processes and coordinating release schedules
- Experience selling enterprise software or cloud-based applications
- Experience explaining complex technical concepts to various business and technical audiences
- Experience presenting to both technical and non-technical executive audiences
- Experience leading complex, multi-year initiatives that may be cross-functional and/or span business and technology- Experience interpreting data and making business recommendations across leadership and cross-functional teams
- Experience working with open data architectures and multi-engine analytics ecosystems
- Experience partnering across product, field, and partner organizations to drive large-scale GTM initiatives
- Experience influencing product direction through customer and market feedback
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
USA, CA, San Diego - 147,900.00 - 200,100.00 USD annually
USA, WA, Seattle - 147,900.00 - 200,100.00 USD annually
Technical Focus:
DynamoDB architecture: single-digit millisecond reads/writes at any scale, on-demand vs. provisioned capacity modes, global tables for multi-region active-active deployments
Data modeling patterns: single-table design, adjacency lists, composite sort keys, GSI overloading, and sparse indexes for complex access patterns
Migration pathways: relational-to-DynamoDB modernization (Oracle/SQL Server/MySQL → DynamoDB), dual-write patterns, CDC-based migration using DMS, and DynamoDB Import for bulk data loading
Integration with AI/ML workloads: DynamoDB as session state, vector metadata store, and tool-use data layer for agentic AI architectures (MCP, NL2SQL gateway patterns)
Zero-ETL and streaming: DynamoDB Streams, Kinesis Data Streams integration, export to S3 for analytics, and zero-ETL to Redshift/OpenSearch
Operational excellence: DAX (in-memory caching), TTL-based data lifecycle management, point-in-time recovery, and cost optimization strategies
GTM Characteristics:
Strategic scope: Worldwide motion — define and scale repeatable DynamoDB engagement patterns across geos, segments (ENT, STRAT, SMB), and verticals
Migration-first pipeline: Owns the GTM motion for relational-to-DynamoDB modernization — the highest-ARR pipeline driver for the service
Cross-functional execution: Bridges DynamoDB product/engineering, field specialists, SAs, and account teams to align on unified positioning against competitors (MongoDB Atlas, GCP Firestore/Bigtable, Azure Cosmos DB)
Field enablement: Builds scalable programs — sales plays, migration assessment tools, battle cards, proof points, and field motions that convert discovery into pipeline
Customer engagement: Comfortable in deep technical discovery with architects and engineering leaders; can whiteboard single-table designs, discuss partition key strategies, and articulate why DynamoDB eliminates operational overhead vs. self-managed NoSQL
Pipeline & adoption metrics: Directly accountable for DynamoDB new workload adoption, migration pipeline growth, and cross-service attach (DynamoDB → Streams → analytics)
Competitive positioning: Technical fluency to counter MongoDB ("developer familiarity"), Cosmos DB ("multi-model"), and Firestore ("serverless simplicity") with trust-based differentiation rooted in DynamoDB's operational track record at scale
Data and AI GTM — Senior Worldwide GTM Specialist
Job Summary: The AWS Data and AI GTM team is seeking a Senior Worldwide GTM Specialist to drive cross-service go-to-market strategies that connect AWS's data platform (databases, analytics, storage) with AI/ML workloads — particularly agentic AI, generative AI, and foundation model integration patterns. This role sells across service boundaries, positioning the full AWS data platform as the differentiated foundation for AI-ready enterprises.
Technical Focus:
Data foundations for AI: how databases (Aurora, DynamoDB, Neptune, OpenSearch) and analytics (Redshift, Athena, Glue, EMR) enable retrieval-augmented generation (RAG), vector search, knowledge graphs, and agentic workflows
Agentic AI architecture patterns: MCP (Model Context Protocol), tool-use frameworks, NL2SQL, semantic layers, and AI-database integration
Data quality, governance, and lineage as prerequisites for trustworthy AI outputs
Reverse-attach motion: AI workloads (Bedrock, SageMaker) driving new data platform consumption
Cross-service value prop: zero-ETL pipelines, unified data access, and the platform advantage vs. single-service competitors (Snowflake, Databricks, GCP Spanner/AlloyDB, Azure Fabric)
GTM Characteristics:
Cross-service storytelling: Breaks down service team silos — articulates the unified AWS data platform advantage that no competitor can match at scale (1M+ customers trust AWS databases)
Play-based execution: Operates within structured sales plays (e.g., "Data Foundations for AI" — $653M+ Created ARR) and emerging plays (DAAP / Data and Agentic AI Accelerator Pathways)
Customer maturity model: Engages customers at different stages — from data modernization (crawl) to AI-ready architectures (run) — with stage-appropriate messaging
Competitive positioning: Technical fluency to counter GCP (AlloyDB/Spanner), Azure (Cosmos DB/Fabric), and Snowflake/Databricks with honest, trust-based differentiation
Metrics-driven: Tracks AI attach rates (DB→AI, AI→Data reverse attach), pipeline velocity, and cross-service consumption as success indicators
Field scalability: Builds enablement assets, working sessions, and prospecting day motions that help field teams sell the platform story independently
Key job responsibilities
Develop and execute GTM strategies that accelerate DynamoDB adoption for mission-critical operational workloads — including internet-scale applications, gaming backends, ad-tech platforms, and agentic AI data layers requiring single-digit millisecond latency at any scale.
Drive relational-to-DynamoDB modernization pipeline by defining migration GTM motions (Oracle/SQL Server/MySQL → DynamoDB), building assessment frameworks, and scaling engagement patterns that convert migration discovery into qualified pipeline across ENT, STRAT, and SMB segments.
Position DynamoDB as the default NoSQL choice against competitive alternatives (MongoDB Atlas, Azure Cosmos DB, GCP Firestore/Bigtable) through trust-based differentiation rooted in operational track record, scale economics, and zero-ops architecture.
Identify and scale repeatable customer engagement models — architectural GTM plays for single-table design adoption, global tables multi-region patterns, and DynamoDB-to-analytics integration (Streams, zero-ETL to Redshift/OpenSearch, S3 export) that drive cross-service attach and platform stickiness.
Build scalable field enablement programs including migration playbooks, data modeling workshops, competitive battle cards, proof-of-concept guides, and prospecting day content that equip field specialists and SAs to independently sell DynamoDB modernization.
Partner across AWS database, analytics, AI/ML, and partner organizations to define and operationalize DynamoDB's role in modern architectures — including integration patterns with Bedrock (agentic tool-use), Lambda (event-driven), and streaming services (Kinesis, EventBridge).
Analyze customer adoption trends, competitive dynamics, and market signals (including SIFT insights, PFR demand signals, and field feedback) to identify growth opportunities, influence product roadmap priorities, and refine GTM positioning globally.
Own worldwide metrics and reporting for DynamoDB GTM motions — tracking new workload adoption, migration pipeline velocity, cross-service consumption (DynamoDB → Streams → analytics), and competitive win/loss patterns to inform strategy iterations.
Data and AI GTM — Key Responsibilities
Develop and execute cross-service GTM strategies that position the full AWS data platform (databases, analytics, storage) as the differentiated foundation for AI/ML workloads — including RAG architectures, vector search, knowledge graphs, and agentic AI patterns.
Drive the "Data Foundations for AI" sales play and emerging motions (DAAP / Data and Agentic AI Accelerator Pathways) by defining customer engagement models that connect data modernization to AI readiness across maturity stages (crawl → walk → run).
Position AWS's cross-service platform advantage against unified-story competitors (Snowflake, Databricks, GCP AlloyDB/Spanner, Azure Fabric) — leading with customer trust and adoption scale rather than portfolio breadth, with honest gap acknowledgement where needed.
Identify and scale repeatable AI-attach engagement patterns — reverse-attach motions (Bedrock/SageMaker → new data consumption), NL2SQL gateway patterns, MCP-based agentic integrations, and semantic layer strategies that drive platform-wide ARR growth.
Build scalable field enablement and positioning for cross-service storytelling — sales plays, working sessions, architecture decision guides, and prospecting day motions that help field teams sell across service boundaries (not within silos).
Partner across AWS database, analytics, AI/ML, and storage teams to break down organizational boundaries and operationalize the platform story — aligning GTM messaging, joint customer engagements, and integrated pipeline motions that reflect how customers actually buy.
Analyze AI-attach rates, pipeline velocity, competitive dynamics, and SIFT field signals to identify growth opportunities, quantify the data-to-AI pipeline, and influence GTM priorities across the Data and AI organization.
Own worldwide metrics for Data and AI GTM motions — tracking DB→AI attach, AI→Data reverse attach, cross-service consumption, and play-level ARR (Created/Launched) to inform leadership decisions and strategy iterations.
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.- 5+ years of Go-To-Market, Business Development, Sales, or Consulting experience
- 5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Experience developing strategies that influence leadership decisions at the organizational level
- Experience managing programs across cross functional teams, building processes and coordinating release schedules
- Experience selling enterprise software or cloud-based applications
- Experience explaining complex technical concepts to various business and technical audiences
- Experience presenting to both technical and non-technical executive audiences
- Experience leading complex, multi-year initiatives that may be cross-functional and/or span business and technology- Experience interpreting data and making business recommendations across leadership and cross-functional teams
- Experience working with open data architectures and multi-engine analytics ecosystems
- Experience partnering across product, field, and partner organizations to drive large-scale GTM initiatives
- Experience influencing product direction through customer and market feedback
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, San Diego - 147,900.00 - 200,100.00 USD annually
USA, WA, Seattle - 147,900.00 - 200,100.00 USD annually
Data & ML pay context
Based on 1,541 disclosed Data & ML salaries on RoleSuite, the role pays a median of $162K/year, with most offers between $127K and $201K (10th–90th percentile: $106K–$244K).
See the full Data & ML salary breakdown →