LiquidStack
Account-Based Marketing (ABM)
Carrollton, Texas
Sponsorship not specifiedDetected 106 days ago
HubSpotSalesforceSales
About the role
- This is a critical, revenue-driving role responsible for executing multi-channel demand generation and ABM programs that directly impact pipeline and revenue.
Responsibilities
- Build and execute multi-channel B2B demand generation campaigns (paid media, email, display, retargeting)
- Develop and manage ABM programs aligned to target accounts and sales priorities
- Create and optimize multi-touch nurture journeys from first engagement through MQL
- Drive consistent delivery of high-quality MQLs
- Monitor and optimize campaigns based on pipeline creation and conversion
- Manage and optimize paid campaigns (Google, LinkedIn, programmatic)
- Partner closely with inside sales to provide lead intelligence and campaign insights
- Support BANT-based qualification and ensure smooth handoff into Salesforce pipeline
Requirements
- 3-5+ years of experience in demand generation, ABM, or lifecycle marketing
- Experience in B2B or enterprise environments
- Hands-on experience with HubSpot (or similar marketing automation platforms)
- Experience managing paid media campaigns (Google, LinkedIn, etc.)
- Strong understanding of lead lifecycle, funnel metrics, and conversion optimization
- Experience in data center, infrastructure, SaaS, or industrial technology industries
- Familiarity with Salesforce and attribution tools
- Experience working closely with inside sales teams
- Ability to work independently and manage multiple campaigns simultaneously
- Increased MQL volume and quality
- Measurable pipeline growth and improved conversion rates
- Strong alignment between marketing and sales
- Scalable, repeatable demand generation programs
- Competitive pay with opportunities for overtime
Benefits
- Paid time off, holidays, and great benefits
Company info
- Be part of an industry-disrupting company with room to grow
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This listing is sourced directly from LiquidStack's careers page and normalized into a canonical job model.