Technical Product Marketing Manager
for section headings. Use - for any list of duties/requirements/benefits. Use
for prose.
We must not repeat job title as heading. No Job ID.
We need to preserve all substantive information; remove boilerplate like EEO, navigation, cookie, legal, duplicated lines. Also remove "Equal opportunity employer" etc. Also remove "Our CRAFT" maybe? It's values but could be considered substantive? It's not a standard heading; but we could include as a section maybe "Our CRAFT" but not in prescribed headings list. The instruction says use headings for those specific headings only. It says "use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It implies we should use those headings if we have content. Other headings not in list maybe not needed. Safer to stick to those headings only. So we will have sections: About the role (maybe corresponds to Role Overview), Responsibilities (What You'll Work On), Requirements (maybe combine What You Bring minimum years etc), Qualifications (maybe technical fluency etc), Skills (maybe list of specific skills). We need to parse the content.
Let's extract:
Company description: "We are WisdomAI. We exist to help people unlock clarity from complexity. WisdomAI builds AI-powered analytics that put answers directly in the hands of the people closest to the business. Our platform doesn’t just surface insights — it explains the why behind them, helping teams move from data to decisions with speed, confidence, and context. We’re trusted by companies like Cisco, Patreon, and Rubrik — and we’re just getting started.The problems here are hard, and the expectations are high. Our team is energized by both. If you’re compelled by ambitious problems, high standards, and meaningful ownership, you’ll thrive here."
That's about the company; could be placed under "About the role"? Actually "About the role" is about the role, not company. But we have no explicit "About the role" heading; we have "Role Overview". That could be considered About the role. So we put Role Overview content under About the role
.
Then "What You'll Work On" is responsibilities. So Responsibilities
with list items.
Then "What You Bring" includes minimum 5 years experience, genuine technical fluency, hands-on ability, working understanding of LLM- and agent-based systems, proven ability to break down complex AI and data concepts, portfolio of GTM assets, experience partnering with product and sales teams, strong research muscle, bias for clarity, speed, narrative excellence. That's a mix of requirements, qualifications, skills. We need to split into Requirements, Qualifications, Skills as per headings. But we can also combine if content thin? The instruction: Prefer a few substantive sections over many thin ones. So we could combine into one section maybe "Requirements" covering all. But we have headings for Requirements, Qualifications, Skills. We could decide to use only Requirements and maybe Skills if we can differentiate. However we must not create sections with filler. If we split arbitrarily, we might end up with thin sections. Better to have one substantive section "Requirements" that includes all. Or we could have "Requirements" for minimum years and experience, "Qualifications" for technical fluency etc, "Skills" for specific tools. But that may be okay if each has substantive content.
Let's see content:
- Minimum 5 years in Product Marketing, Technical Product Marketing, or an adjacent technical GTM role (Solutions Engineering, Analytics Engineering, Technical Evangelism) in Data, Analytics, BI, or AI software — Snowflake, Databricks, BigQuery, AWS, Power BI, Tableau, Looker, Sigma, Omni, dbt, or similar. => requirement.
- Genuine technical fluency: you can write SQL, reason about data models and semantic layers, read a reference architecture, and hold your own in a conversation with a data engineer. => qualification/skill.
- Hands-on ability to build and run your own demos and technical content without waiting on an SE. => skill.
- Working understanding of LLM- and agent-based systems and how they get evaluated for accuracy, trust, and governance in an enterprise data context. => qualification.
- Proven ability to break down complex AI and data concepts into clear, concise messaging. => skill.
- Portfolio of GTM assets: pitch decks, competitive teardowns, launch plans, demo narratives, and technical content aimed at user, manager, and executive buyers. => qualification/experience.
- Experience partnering with product and sales teams in fast-moving environments. => experience.
- Strong research muscle: customer interviews, workflow mapping, persona creation, competitive analysis. => skill.
- A bias for clarity, speed, and narrative excellence. => attribute.
We could group: Requirements: minimum 5 years experience. Qualifications: technical fluency, LLM understanding, portfolio, partnering experience. Skills: SQL, data modeling, demo building, breaking down concepts, research muscle, bias for clarity etc. But many overlap.
Given instruction to prefer few substantive sections, maybe we just have one section "Requirements" that includes all bullet points. That would be substantive.
Thus sections: About the role (Role Overview), Responsibilities (What You'll Work On), Requirements (What You Bring). Possibly also "Why This Role Matters" but not in list; we could omit.
We must not include Pay/Benefits/Schedule as they are not present.
Now we need to format.
We'll produce:
About the role
Role Overview content...
Then Responsibilities
- ... each bullet from What You'll Work On
Then Requirements
- ... each bullet from What You Bring
We need to preserve all substantive information; not invent or summarize away detail. So we must keep the details exactly as in text, but we can rephrase slightly? The instruction: preserve ALL substantive information; do NOT invent or summarize away detail. So we should keep the meaning but can we rephrase? Safer to keep sentences similar but we can adjust for list items.
Let's extract Role Overview paragraph:
"We're looking for a Technical Product Marketing Manager who is equal parts engineer-brain and storyteller — someone who can sit in a working session with a data engineering team, understand how they model, govern, and query their warehouse, and then turn that understanding into messaging, demos, and content that moves analytics leaders, data teams, and business users to adopt WisdomAI. This is a hands-on, technical seat. You'll go deep on the product and the stack around it — warehouses, semantic layers, BI tools, agentic AI — and be the person who can both build the demo and write the narrative that frames it on Monday, and later the same week write the technical white paper or jump on a sales call to handle a competitive objection with the data team. You'll be a full-stack product marketing, working across product launches, website content (product, solutions, industry), technical enablement, campaigns, and competitive strategy. As we build the team there will be room for increased specialization. Today, as a Series A company moving fast, we need a "get it done" team player who is low on ego and high on agency, with a real passion for collaboration across Product, Engineering, Sales, and Success."
We'll put that in .
Now Responsibilities list from "What You'll Work On":
- Technical Positioning & Messaging
Build and evolve WisdomAI's core messaging anchored in data team workflows and technical realities, not feature lists. Translate how the product actually works — context engineering, semantic modeling, query generation, agent reasoning, governance, deployment — into value propositions that land with both a data architect and a CFO. Maintain the messaging hierarchy that keeps product, sales, and marketing telling one consistent story.
- Technical Audience Research & Insights
Run continuous qualitative and quantitative research with data engineers, analytics engineers, BI owners, and platform architects to map workflows, tooling, pain points, and decision criteria. Build and maintain personas and ICP definitions (analytics leaders, BI/platform owners, data engineering, RevOps, FP&A, product teams). Serve as the internal expert on how technical buyers evaluate, pilot, adopt, and expand — including what happens inside a POC or bake-off.
- Product Launch Strategy
Own end-to-end launches for major features, capabilities, and platform releases. Pair every launch narrative with the technical substance that makes it credible: architecture explainers, docs-quality feature detail, demo flows, and reference use cases. Partner with Product, Engineering, Design, and Marketing to deliver multi-channel launch programs.
- Video Demos, Technical Content & Proof
Build and maintain the video demo assets, sample datasets, and reference scenarios that show the product doing real work on realistic data. Produce technical content that earns credibility with practitioners: solution briefs, architecture and integration explainers, benchmark and evaluation write-ups, technical blogs, and video walkthroughs. Partner with Solutions Engineering to turn repeatable POC patterns into reusable, scalable assets.
- Competitive & Market Intelligence
Maintain a live view of how competitors — legacy BI, modern BI, warehouse-native AI, and AI analytics startups — actually solve problems for the same audience. Build "Why Wisdom vs. X" narratives grounded in architecture, workflow, and outcomes, backed by hands-on teardowns and head-to-head evaluation where possible. Enable Sales, SE, and Product with competitive insight that holds up under technical scrutiny.
- Sales & GTM Enablement
Build pitch decks, playbooks, objection handling guides, technical FAQs, and customer stories aligned to the real-world stack our audience runs. Equip Sales, Solutions Engineering, and Customer Success with the messaging, proof points, and demo narratives they need to win technical evaluations.
- Content Strategy & Thought Leadership
Develop full-funnel content that shows how WisdomAI improves the whole workflow: Analytics → Insights → Decisions → Actions → ROI. Collaborate with the Head of Product Marketing and company leaders to articulate our category POV. Cover the broader interests of the data and analytics audience — not just our feature set.
- Cross-functional Partnership
Act as the connective tissue between Product, Engineering, Sales, Success, and Marketing. Bring the voice of the technical customer into roadmap, positioning, and prioritization. Ensure customer feedback, audience insight, and competitive intelligence flow across the company.
We need to turn each into
- items. Could keep the heading bold? But we just need list items; we can include the heading as part of the li text.
Now Requirements list from "What You Bring":
- Minimum 5 years in Product Marketing, Technical Product Marketing, or an adjacent technical GTM role (Solutions Engineering, Analytics Engineering, Technical Evangelism) in Data, Analytics, BI, or AI software — Snowflake, Databricks, BigQuery, AWS, Power BI, Tableau, Looker, Sigma, Omni, dbt, or similar.
- Genuine technical fluency: you can write SQL, reason about data models and semantic layers, read a reference architecture, and hold your own in a conversation with a data engineer.
- Hands-on ability to build and run your own demos and technical content without waiting on an SE.
- Working understanding of LLM- and agent-based systems and how they get evaluated for accuracy, trust, and governance in an enterprise data context.
- Proven ability to break down complex AI and data concepts
for prose. We must not repeat job title as heading. No Job ID. We need to preserve all substantive information; remove boilerplate like EEO, navigation, cookie, legal, duplicated lines. Also remove "Equal opportunity employer" etc. Also remove "Our CRAFT" maybe? It's values but could be considered substantive? It's not a standard heading; but we could include as a section maybe "Our CRAFT" but not in prescribed headings list. The instruction says use headings for those specific headings only. It says "use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It implies we should use those headings if we have content. Other headings not in list maybe not needed. Safer to stick to those headings only. So we will have sections: About the role (maybe corresponds to Role Overview), Responsibilities (What You'll Work On), Requirements (maybe combine What You Bring minimum years etc), Qualifications (maybe technical fluency etc), Skills (maybe list of specific skills). We need to parse the content.
Let's extract:
Company description: "We are WisdomAI. We exist to help people unlock clarity from complexity. WisdomAI builds AI-powered analytics that put answers directly in the hands of the people closest to the business. Our platform doesn’t just surface insights — it explains the why behind them, helping teams move from data to decisions with speed, confidence, and context. We’re trusted by companies like Cisco, Patreon, and Rubrik — and we’re just getting started.The problems here are hard, and the expectations are high. Our team is energized by both. If you’re compelled by ambitious problems, high standards, and meaningful ownership, you’ll thrive here."
That's about the company; could be placed under "About the role"? Actually "About the role" is about the role, not company. But we have no explicit "About the role" heading; we have "Role Overview". That could be considered About the role. So we put Role Overview content under About the role
.
Then "What You'll Work On" is responsibilities. So Responsibilities
with list items.
Then "What You Bring" includes minimum 5 years experience, genuine technical fluency, hands-on ability, working understanding of LLM- and agent-based systems, proven ability to break down complex AI and data concepts, portfolio of GTM assets, experience partnering with product and sales teams, strong research muscle, bias for clarity, speed, narrative excellence. That's a mix of requirements, qualifications, skills. We need to split into Requirements, Qualifications, Skills as per headings. But we can also combine if content thin? The instruction: Prefer a few substantive sections over many thin ones. So we could combine into one section maybe "Requirements" covering all. But we have headings for Requirements, Qualifications, Skills. We could decide to use only Requirements and maybe Skills if we can differentiate. However we must not create sections with filler. If we split arbitrarily, we might end up with thin sections. Better to have one substantive section "Requirements" that includes all. Or we could have "Requirements" for minimum years and experience, "Qualifications" for technical fluency etc, "Skills" for specific tools. But that may be okay if each has substantive content.
Let's see content:
- Minimum 5 years in Product Marketing, Technical Product Marketing, or an adjacent technical GTM role (Solutions Engineering, Analytics Engineering, Technical Evangelism) in Data, Analytics, BI, or AI software — Snowflake, Databricks, BigQuery, AWS, Power BI, Tableau, Looker, Sigma, Omni, dbt, or similar. => requirement.
- Genuine technical fluency: you can write SQL, reason about data models and semantic layers, read a reference architecture, and hold your own in a conversation with a data engineer. => qualification/skill.
- Hands-on ability to build and run your own demos and technical content without waiting on an SE. => skill.
- Working understanding of LLM- and agent-based systems and how they get evaluated for accuracy, trust, and governance in an enterprise data context. => qualification.
- Proven ability to break down complex AI and data concepts into clear, concise messaging. => skill.
- Portfolio of GTM assets: pitch decks, competitive teardowns, launch plans, demo narratives, and technical content aimed at user, manager, and executive buyers. => qualification/experience.
- Experience partnering with product and sales teams in fast-moving environments. => experience.
- Strong research muscle: customer interviews, workflow mapping, persona creation, competitive analysis. => skill.
- A bias for clarity, speed, and narrative excellence. => attribute.
We could group: Requirements: minimum 5 years experience. Qualifications: technical fluency, LLM understanding, portfolio, partnering experience. Skills: SQL, data modeling, demo building, breaking down concepts, research muscle, bias for clarity etc. But many overlap.
Given instruction to prefer few substantive sections, maybe we just have one section "Requirements" that includes all bullet points. That would be substantive.
Thus sections: About the role (Role Overview), Responsibilities (What You'll Work On), Requirements (What You Bring). Possibly also "Why This Role Matters" but not in list; we could omit.
We must not include Pay/Benefits/Schedule as they are not present.
Now we need to format.
We'll produce:
About the role
Role Overview content...
ThenResponsibilities
- ... each bullet from What You'll Work On
Requirements
- ... each bullet from What You Bring
. Now Responsibilities list from "What You'll Work On": - Technical Positioning & Messaging Build and evolve WisdomAI's core messaging anchored in data team workflows and technical realities, not feature lists. Translate how the product actually works — context engineering, semantic modeling, query generation, agent reasoning, governance, deployment — into value propositions that land with both a data architect and a CFO. Maintain the messaging hierarchy that keeps product, sales, and marketing telling one consistent story. - Technical Audience Research & Insights Run continuous qualitative and quantitative research with data engineers, analytics engineers, BI owners, and platform architects to map workflows, tooling, pain points, and decision criteria. Build and maintain personas and ICP definitions (analytics leaders, BI/platform owners, data engineering, RevOps, FP&A, product teams). Serve as the internal expert on how technical buyers evaluate, pilot, adopt, and expand — including what happens inside a POC or bake-off. - Product Launch Strategy Own end-to-end launches for major features, capabilities, and platform releases. Pair every launch narrative with the technical substance that makes it credible: architecture explainers, docs-quality feature detail, demo flows, and reference use cases. Partner with Product, Engineering, Design, and Marketing to deliver multi-channel launch programs. - Video Demos, Technical Content & Proof Build and maintain the video demo assets, sample datasets, and reference scenarios that show the product doing real work on realistic data. Produce technical content that earns credibility with practitioners: solution briefs, architecture and integration explainers, benchmark and evaluation write-ups, technical blogs, and video walkthroughs. Partner with Solutions Engineering to turn repeatable POC patterns into reusable, scalable assets. - Competitive & Market Intelligence Maintain a live view of how competitors — legacy BI, modern BI, warehouse-native AI, and AI analytics startups — actually solve problems for the same audience. Build "Why Wisdom vs. X" narratives grounded in architecture, workflow, and outcomes, backed by hands-on teardowns and head-to-head evaluation where possible. Enable Sales, SE, and Product with competitive insight that holds up under technical scrutiny. - Sales & GTM Enablement Build pitch decks, playbooks, objection handling guides, technical FAQs, and customer stories aligned to the real-world stack our audience runs. Equip Sales, Solutions Engineering, and Customer Success with the messaging, proof points, and demo narratives they need to win technical evaluations. - Content Strategy & Thought Leadership Develop full-funnel content that shows how WisdomAI improves the whole workflow: Analytics → Insights → Decisions → Actions → ROI. Collaborate with the Head of Product Marketing and company leaders to articulate our category POV. Cover the broader interests of the data and analytics audience — not just our feature set. - Cross-functional Partnership Act as the connective tissue between Product, Engineering, Sales, Success, and Marketing. Bring the voice of the technical customer into roadmap, positioning, and prioritization. Ensure customer feedback, audience insight, and competitive intelligence flow across the company. We need to turn each into