Sales Manager (Cloud & Data sales Hunter)

Salary Range: $170K – $200K
Solution SellingEnterpriseEnterprise DealLongNorth AmericaBuild TeamEquity
Tools: AwsAzureGcp

Data \& AI Sales Hunter – US

Location: USA – Central \& East Coast \| Remote

Experience: 10–12 Years

Base Salary: $200K–$250K

Employment Type: Full\-time

About the Role:

We are looking for a senior Data \& AI Sales Hunter to drive new business and enterprise client acquisition across the US market.

This is a hunter\-focused enterprise sales role, responsible for building a self\-generated pipeline, acquiring new logos, engaging senior decision\-makers, and managing opportunities through the complete sales cycle—from prospecting and proposal to negotiation and closure.

Key Responsibilities

\* Identify, prospect, and acquire new enterprise clients / new logos across the US.

\* Build and manage a strong self\-generated sales pipeline.

\* Sell Data \& AI technology services and solutions to large enterprise organizations.

\* Build relationships with CIOs, CDOs, CTOs, VP Data, VP Engineering, Procurement/Sourcing, and other senior stakeholders.

\* Own opportunities through prospecting, discovery, proposal, negotiation, and closure.

\* Partner with technical and pre\-sales teams to develop effective solution propositions.

\* Understand client business challenges and articulate the business value of Data \& AI solutions.

\* Own sales quotas and consistently deliver against revenue targets.

\* Leverage an established US enterprise network to generate new opportunities.

Required Experience

\* 14–17 years of total professional experience in enterprise sales / business development.

\* 5–7\+ years of experience specifically selling Data \& AI, Analytics, Cloud, or technology services.

\* Strong US enterprise sales experience with a proven new\-business hunting track record.

\* Demonstrated success in personally acquiring net\-new enterprise clients.

\* Strong existing network among senior US enterprise decision\-makers.

\* Experience handling large and complex enterprise deals.

\* Proven track record of meeting or exceeding sales quotas.

\* Strong consultative selling, negotiation, and relationship\-building skills.

\* Relevant Solution Experience

Commercial experience selling solutions/services in areas such as:

\* Data Engineering

\* Data Platforms

\* Data Modernization

\* Analytics

\* AI / Machine Learning

\* Generative AI

\* Cloud

\* Databricks

\* Snowflake

\* AWS / Azure / GCP

Candidates do not need to be hands\-on technical engineers but must understand Data \& AI solutions well enough to sell their business value to enterprise clients.

Ideal Candidate

\* The ideal candidate will demonstrate:

\* Proven hunter / new\-logo acquisition track record

\* Self\-generated pipeline development

\* Strong US enterprise relationships

\* Access to C\-level decision\-makers

\* Data \& AI services sales experience

\* Large/complex enterprise deal closures

\* Clear quota ownership and measurable achievement

\* Experience working with technical/pre\-sales teams

Important:

US candidates only. Candidates must currently be based in the USA, with preference for the Central and East Coast regions.

Candidates primarily focused on account management/farming, inbound leads, RFP\-driven sales, or existing\-client management will not be considered.

Pay: $170,000\.00 \- $200,000\.00 per year

Application Question(s):

* How many years of experience do you have selling Data / Data Engineering / Data Platform services?
* How many years of experience do you have as a hands\-on individual contributor / hunter acquiring net\-new US enterprise clients?
* Have you personally sold Databricks, Snowflake, and AWS/Azure/GCP\-based Data solutions? Please specify.
* What was your annual sales quota and percentage achieved in your current/most recent role?
* Number of net\-new logos acquired:
* Key US industries you have worked in:
* Largest net\-new deal:
* Current Annual Salary
* Expected Annual Salary
* Notice Period
* Current Location

Work Location: Remote

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