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Founding GTM & B2B Sales Lead

CompraTica Empleos

EMP:Sales
Berlin
Tiempo Completo
Remoto
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Descripción

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the RoleThis is a rare opportunity to be the first dedicated GTM and B2B Sales hire at a fast-moving preventive healthtech company

You won't be running plays from an existing playbook — you'll be writing it.

If you thrive in zero-to-one environments, love building pipeline with modern tooling, and want real commercial ownership, this role was designed for you.

The company offers a membership-based personalized health platform built around comprehensive biomarker testing (100+ markers), clinician-reviewed insights, and year-round concierge support.

On the B2B side, the platform powers a Diagnostics-as-a-Service offering — including an API and white-label capabilities — targeting employers, insurers, clinics, corporate wellness programs, and location partners.

You'll work directly with the founding team to build and own the entire revenue motion from scratch.

What You'll DoBuild and own the B2B pipeline end-to-end — outbound prospecting, partnership development, and inbound conversion.

Run the full sales cycle: discovery → demo → negotiation → close, with deal sizes ranging from €10k to €500k+.

Define and execute the go-to-market strategy for B2B channels, including employers, insurers, clinics, and corporate wellness buyers.

Set up the sales stack from zero — CRM, data enrichment, automation workflows, and intent signals.

Partner directly with founders on ICP definition, pricing strategy, and packaging decisions.

Feed real market signal back into product and business strategy.

What We're Looking ForRequired:2–6 years of B2B sales or GTM experience, ideally in healthtech, corporate.

Beneficios

, diagnostics, or a related sector.Native or fully fluent German speaker — this is a hard requirement for this role.Proven ability to self-source pipeline; you don't need an SDR feeding you leads.Hands-on experience with modern sales tooling (e.g

CRM, enrichment tools, outbound automation).

Comfortable operating in an early-stage, high-ambiguity environment with minimal structure.

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