Technical Marketing Manager, Data & AI Platforms

Job Description

Job Description

Reports to CMO 

Why this role exists

You provide the technical proof that xLake Data & AI Platform is real. You build the demos, sample applications, and talks that make the platform's hardest claims undeniable to enterprise data architects, enterprise architects, and AI practitioners. You win the architects before the sales call: the ones in the audience, the ones debating the reference architecture, the ones deciding whether Acceldata is real before anyone from sales has said a word.

What you'll do

Build the proof (sample applications and demos)
-- Build and maintain working sample applications and reference implementations on xLake that make the value self-evident: an agent runtime scheduled across cloud and on-prem, an MCP-driven agent scenario on governed data, multi-engine observability tracing a failure back to upstream lineage and pipeline health.
-- Package these into repeatable, runnable demo assets the field and marketing can deliver without you in the room.

-- Keep demos current as the platform ships.

Create technical material for a technical buyer

--Author reference architectures, technical deep-dives, solution briefs, benchmarks, and whitepapers aimed at three distinct audiences: data architects (lineage, governance, pipeline health), enterprise architects (cross-environment control plane, no consolidation), and AI practitioners (governed data for agents, model-agnostic runtimes). Each is a different dialect; you write all three credibly.
--Own the technical framework behind the positioning: control without consolidation, runtime versus design-time governance, multi-engine observability, source- and model-agnostic interoperability. Provide proof through demos, papers and talks.

Represent Acceldata in the field
-- Run live platform demos at tradeshows and events, and support SDRs on early-stage screening and qualification calls, the top-of-funnel demo that helps sort real prospects from noise, distinct from the deal-stage evaluation the Sales Engineer owns.
-- Build and deliver conference sessions and technical presentations; speak on stage.

Power product launches and announcements
-- Own the technical proof for every major launch and GA: the demo that shows the new capability working, the reference architecture that explains it to architects, and the launch talk or session.
-- Turn new platform capabilities into credible technical narrative fast, translate what shipped into why it matters for data architects, enterprise architects, and AI practitioners.
-- Partner with product marketing and product management so the technical story lands on day one.

Standard technical marketing
-- Partner with product marketing, product management, sales engineering, and developer relations on launch content, competitive technical positioning, and sales enablement.
-- Carry field and practitioner signal back into product and positioning.

What winning looks like (first 6 to 12 months)

-- A library of live, runnable demos spanning the three solutions (Data & Analytics, Data Observability & ADM, AI & Applications).
-- 10 in-person/online conference talks delivered to architect and practitioner audiences.
-- The field actively uses the sample apps and other technical material in sales pursuits.

Bonus

-- Domain background in data observability, data management, or governance.
-- Existing conference speaking track record.
-- Has previously built demos or sample apps for a platform (not point-tool) product.

Who you are

-- Hands-on: you build, you don't just describe. Comfortable across data engines (Spark, streaming, warehouses, lakes), Kubernetes, APIs, and modern AI/agent tooling (LLM APIs, MCP, agent frameworks).
-- Can hold a room of data architects and a room of AI practitioners with equal credibility.
Strong writer and presenter with genuine stage presence.
-- 12+ years in technical marketing engineering, developer relations, solutions/sales engineering, or a hands-on architect role.

If you’re passionate about translating deep technology into market impact, we’d love to have you on the team.

This role requires on-site presence at HQ three days a week.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.