Sr. Manager, Business Development – Data Services (Analytics & Storage), SSO (Service Specialist Orgnization)
Amazon Web Services•Published 1 days ago•First seen 17 hours ago
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Would you like to lead a high-performing specialist organization driving revenue growth, product adoption, and market leadership for the AWS Analytics and Storage portfolios? Would you like to be part of a specialist organization that turns deep product expertise into scaled field execution — accelerating how enterprise, digital-native, and startup customers modernize their data estate? Do you have the product depth, market instinct, and enablement discipline to further establish AWS as the undisputed leader in cloud data services?
As the Sr. Manager, Data Services, you will own the strategy and execution for two of the most strategically connected portfolios in AWS: Analytics — the layer where customers derive value from data — and Storage — the foundation on which that data lives. Bringing these teams under single leadership is deliberate: modern data architectures (lakehouse, zero-ETL, open table formats and Agentic AI data pipelines) collapse the traditional boundary between storage and analytics. You will be accountable for a unified data services narrative, a single go-to-market motion, and a shared enablement engine that makes the whole greater than the sum of its parts.
This is fundamentally a scale role. Success is not measured by the deals you personally close, but by the leverage you create: your ability to take one proven win, convert it into a repeatable play, enable a hundred sellers to run it, and drive a thousand customer adoptions from it. We are looking for a leader who is a genuine product person at heart — someone who reads the roadmap, forms an independent point of view on where the market is heading, and can teach that point of view to others at scale.
The ideal candidate combines a pre-sales / solutions pedigree with the business judgment to engage at the CxO/VP level and the technical credibility to hold their own with data engineers, platform architects, DBAs, and developers. You should demonstrate the ability to think strategically and analytically about business, product, and technical challenges, build and convey compelling value propositions, and work cross-organizationally to build consensus. A strong sense of ownership, bias for action, and the ability to deliver results in ambiguity is essential.
What Makes This Role Different
Beyond the standard specialist leadership mandate, we are hiring against four differentiating capabilities. Candidates will be assessed explicitly against each.
1. Deep product understanding, not surface familiarity: You can explain not just what a service does, but why it is architected that way, where its boundaries are, when a competitor is genuinely better, and how the roadmap changes the answer six months out. You are expected to hold a defensible technical opinion in front of both a customer architect and a service GM.
2. Sharp market and technology trend sensing: You track the data ecosystem — open table formats, lakehouse convergence, zero-ETL, vector and agentic data access patterns, data governance and sovereignty, storage economics and tiering, the competitive moves of hyperscalers and independent data platforms. You translate weak signals into early GTM bets before they become obvious, and you are willing to be accountable for those calls. You should be also very close to market trend and product iterations from other CSPs and big logos (e.g. Databricks).
3. Field guidance that changes outcomes: You do not simply relay headquarters messaging. You sit with account teams on real opportunities, diagnose why deals stall, prescribe the specific technical and commercial path forward, and then generalize that diagnosis into guidance the rest of the field can use.
4. The 1 → 100 → 1000 enablement flywheel: This is the core operating model of the role: prove the pattern once (1 lighthouse win), codify and transfer it to the field (enable 100 sellers and SAs), and harvest it at scale (drive 1000 customer adoptions). You are expected to design this mechanism, instrument it, and report on conversion at each stage.
Key job responsibilities
Team Leadership & Organizational Strategy
▪ Lead, develop, and retain the Analytics and Storage specialist teams (Go-to-Market Specialists + SSAs); define a unified data services strategy that eliminates internal seams and drives business growth.
▪ Build talent bar and succession depth; own the portfolio coverage model — deciding which services, segments, and accounts get specialist attention versus scaled or partner-led mechanisms.
Product Depth & Roadmap Influence
▪ Maintain deep expertise across the Analytics and Storage portfolios; serve as the region's trusted voice on capability, gaps, and competitive positioning; translate field reality into prioritized roadmap asks to service GMs/VPs and close the loop back to sellers when the roadmap moves.
Business Development & Pipeline Execution
▪ Set and execute a business development plan driving pipeline generation, revenue growth, and service adoption; guide the front line on live opportunities — qualifying, shaping the technical approach, and unblocking competitive and commercial obstacles.
Executive Communication & Data-Driven Management
▪ Prepare and deliver data-driven business reviews to senior leadership; leverage Salesforce and internal systems to track pipeline, analyze performance, and build investment cases.
▪ Set and manage annual and multi-year growth targets with clear articulation of the specific drivers behind sustainable growth.
A day in the life
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.
Would you like to lead a high-performing specialist organization driving revenue growth, product adoption, and market leadership for the AWS Analytics and Storage portfolios? Would you like to be part of a specialist organization that turns deep product expertise into scaled field execution — accelerating how enterprise, digital-native, and startup customers modernize their data estate? Do you have the product depth, market instinct, and enablement discipline to further establish AWS as the undisputed leader in cloud data services?
As the Sr. Manager, Data Services, you will own the strategy and execution for two of the most strategically connected portfolios in AWS: Analytics — the layer where customers derive value from data — and Storage — the foundation on which that data lives. Bringing these teams under single leadership is deliberate: modern data architectures (lakehouse, zero-ETL, open table formats and Agentic AI data pipelines) collapse the traditional boundary between storage and analytics. You will be accountable for a unified data services narrative, a single go-to-market motion, and a shared enablement engine that makes the whole greater than the sum of its parts.
This is fundamentally a scale role. Success is not measured by the deals you personally close, but by the leverage you create: your ability to take one proven win, convert it into a repeatable play, enable a hundred sellers to run it, and drive a thousand customer adoptions from it. We are looking for a leader who is a genuine product person at heart — someone who reads the roadmap, forms an independent point of view on where the market is heading, and can teach that point of view to others at scale.
The ideal candidate combines a pre-sales / solutions pedigree with the business judgment to engage at the CxO/VP level and the technical credibility to hold their own with data engineers, platform architects, DBAs, and developers. You should demonstrate the ability to think strategically and analytically about business, product, and technical challenges, build and convey compelling value propositions, and work cross-organizationally to build consensus. A strong sense of ownership, bias for action, and the ability to deliver results in ambiguity is essential.
What Makes This Role Different
Beyond the standard specialist leadership mandate, we are hiring against four differentiating capabilities. Candidates will be assessed explicitly against each.
1. Deep product understanding, not surface familiarity: You can explain not just what a service does, but why it is architected that way, where its boundaries are, when a competitor is genuinely better, and how the roadmap changes the answer six months out. You are expected to hold a defensible technical opinion in front of both a customer architect and a service GM.
2. Sharp market and technology trend sensing: You track the data ecosystem — open table formats, lakehouse convergence, zero-ETL, vector and agentic data access patterns, data governance and sovereignty, storage economics and tiering, the competitive moves of hyperscalers and independent data platforms. You translate weak signals into early GTM bets before they become obvious, and you are willing to be accountable for those calls. You should be also very close to market trend and product iterations from other CSPs and big logos (e.g. Databricks).
3. Field guidance that changes outcomes: You do not simply relay headquarters messaging. You sit with account teams on real opportunities, diagnose why deals stall, prescribe the specific technical and commercial path forward, and then generalize that diagnosis into guidance the rest of the field can use.
4. The 1 → 100 → 1000 enablement flywheel: This is the core operating model of the role: prove the pattern once (1 lighthouse win), codify and transfer it to the field (enable 100 sellers and SAs), and harvest it at scale (drive 1000 customer adoptions). You are expected to design this mechanism, instrument it, and report on conversion at each stage.
Key job responsibilities
Team Leadership & Organizational Strategy
▪ Lead, develop, and retain the Analytics and Storage specialist teams (Go-to-Market Specialists + SSAs); define a unified data services strategy that eliminates internal seams and drives business growth.
▪ Build talent bar and succession depth; own the portfolio coverage model — deciding which services, segments, and accounts get specialist attention versus scaled or partner-led mechanisms.
Product Depth & Roadmap Influence
▪ Maintain deep expertise across the Analytics and Storage portfolios; serve as the region's trusted voice on capability, gaps, and competitive positioning; translate field reality into prioritized roadmap asks to service GMs/VPs and close the loop back to sellers when the roadmap moves.
Business Development & Pipeline Execution
▪ Set and execute a business development plan driving pipeline generation, revenue growth, and service adoption; guide the front line on live opportunities — qualifying, shaping the technical approach, and unblocking competitive and commercial obstacles.
Executive Communication & Data-Driven Management
▪ Prepare and deliver data-driven business reviews to senior leadership; leverage Salesforce and internal systems to track pipeline, analyze performance, and build investment cases.
▪ Set and manage annual and multi-year growth targets with clear articulation of the specific drivers behind sustainable growth.
A day in the life
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.
Basic Qualifications
- 5+ years of people management experience
- 10+ years of experience in pre-sales / solutions engineering, business development, or product management in the enterprise cloud or data industry — with a substantial portion in data warehouse, analytics, data platform, or storage solutions. Demonstrated solutions background: a track record of winning the technical argument and designing customer solutions, not solely a quota-carrying or account-management path.
- Deep, demonstrable product knowledge of modern data technologies — data warehousing, data lakes and lakehouse architectures, streaming and ETL/ELT, open table and file formats, object and block storage, backup and data protection.
- Proven success building and running scaled enablement: demonstrable examples of taking a repeatable motion from a single win to broad field execution, with metrics to evidence it.
- Bachelor's degree in Computer Science, Engineering, or a related technical field; strong verbal and written communication skills with the ability to engage credibly with both senior executives and technical practitioners; experience working in a global matrix environment.
Preferred Qualifications
- Advanced degree (Master's or MBA) in a technical or business discipline.
- Hands-on or architecture-level experience with cloud data platforms and modern data architectures; working knowledge of software development practices and data center, infrastructure, and networking technologies.
- Experience with open-source data ecosystems (Apache Spark, Apache Iceberg, Apache Hudi, Delta Lake, Apache Kafka, Apache Hadoop) and the communities around them.
- Experience influencing product roadmaps as the voice of a region or a major customer segment.
- Experience with account management across Enterprise, digital-native, and startup segments, and strong solution-selling ability.
- Experience leading more than one portfolio or team simultaneously in a global matrix organization, or integrating previously separate teams under a unified strategy.
- Familiarity with AI/ML and generative AI data requirements, and how data platform and storage decisions constrain or enable them.