Databricks Sales Director

Job Description

CEI.AI is seeking a Databricks Sales Director to join our growing organization!

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Industry : CEI – AI Engineering & Transformation Partner, IT Solutions/Consulting, & Enterprise Technology Services

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Job Title : Databricks Solution Sales Leader (Partnerships & Technical Sales)

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Location : Remote – EST/CST preferred; occasional travel to Pittsburgh, PA or other CEI/Client locations as needed .

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Employment Type : W2 Direct Hire / Full Time

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Compensation : Competitive pay (Salary) | Benefits available ( optional ) [Medical, Dental, Vision, and 401(k) match]

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Position Overview :

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CEI is an AI-first engineering and transformation company helping enterprise organizations modernize technology environments and deliver measurable business outcomes through data, cloud, AI, and software engineering solutions. We are seeking a Databricks Solution Sales Leader to drive enterprise growth around Databricks and related Data & AI consulting services. This is a quota-carrying individual contributor sales position for an experienced enterprise seller who can independently develop pipeline, acquire new clients, expand existing relationships, and lead complex consulting/services opportunities from initial discovery through close. The ideal candidate combines a strong background in enterprise consulting or professional services sales with meaningful experience in the Databricks ecosystem. This individual should understand how to identify business problems that can be addressed through data modernization, analytics, and AI solutions; position Databricks within those initiatives; and translate the opportunity into consulting and professional services revenue.

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Required Skills/Experience/Qualifications :

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• Bachelor's Degree required
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• 10+ years of experience in enterprise consulting/services sales within a system integrator or similar environment
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• Proven track record as a quota-carrying individual contributor, with clear ownership of pipeline generation, deal progression, and revenue attainment
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• Demonstrated success closing enterprise consulting engagements ($500K–$5M+), including full lifecycle sales ownership
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• Direct experience selling Databricks-led or data platform consulting services, with the ability to articulate how those services drive business outcomes
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• Strong experience monetizing Databricks within enterprise accounts, including landing initial engagements, expanding into multi-use case environments, and scaling into multi-million-dollar services revenue
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• Experience building net-new pipeline (new logos) while also expanding existing enterprise accounts through land-and-expand strategies
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• Hands-on experience working within the Databricks partner ecosystem, including co-sell alignment, partner engagement, and joint GTM efforts
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• Strong understanding of Lakehouse architecture, data engineering pipelines, analytics workloads, and AI/ML use cases
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• Experience leveraging cloud ecosystems (AWS, Azure, GCP) to support Databricks-related opportunities
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• Ability to engage and influence C-level stakeholders (CIO, CDO, business leaders) and align solutions to business outcomes
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• Clear demonstration of being a revenue-driving seller, not operating primarily as presales, technical support, or alliance-only resource
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Preferred Skills (Not Required) :

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• Experience scaling or contributing to a Databricks-focused practice within a consulting organization
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• Familiarity with Databricks-native capabilities such as MLflow, Unity Catalog, or GenAI-related tooling
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• Experience building or selling accelerators or repeatable solutions tied to data and AI use cases
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• Prior experience working in multi-alliance environments (Databricks, AWS, Google Cloud, Microsoft)
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• Familiarity with technologies and concepts such as Apache Spark, Delta Lake, Snowflake, dbt, data ingestion/ETL/ELT, data governance, DataOps/MLOps, and modern AI/ML frameworks.
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• Exposure to partner programs, Databricks certifications, or influence-based selling motions
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• Experience selling Data & AI solutions across multiple enterprise industries.
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Key Responsibilities :

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Enterprise Sales & Revenue Growth

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• Own and drive revenue growth for Databricks-related consulting and professional services across enterprise accounts.
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• Independently build and manage pipeline through net-new business development, strategic account targeting, relationship development, and expansion of existing accounts.
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• Lead complex, consultative enterprise sales cycles from prospecting and discovery through solution positioning, proposal development, negotiation, and close.
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• Develop land-and-expand strategies that turn initial projects into broader, long-term client relationships and additional use cases.
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• Build relationships with CIOs, CDOs, CTOs, Data & AI leaders, and other executive and business stakeholders.
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• Consistently manage pipeline, forecasting, opportunity progression, and quota attainment.
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Databricks & Solution Selling

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• Identify client needs and position Databricks-led solutions and CEI services around data modernization, data engineering, analytics, AI/ML, and related transformation initiatives.
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• Demonstrate sufficient technical credibility to effectively sell Databricks solutions while partnering with architects, engineers, and delivery teams for deeper technical design.
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• Understand Databricks capabilities and the broader modern data ecosystem well enough to connect technology investments to business value, ROI, KPIs, and measurable outcomes.
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• Work with technical teams to shape solution proposals, proof-of-value engagements, and larger implementation opportunities.
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• Help clients identify opportunities to expand Databricks adoption across additional workloads, use cases, and business units.
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Partner & Ecosystem Collaboration

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• Develop productive relationships with Databricks sales, alliance, and partner teams to support account development and joint opportunities.
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• Collaborate with cloud and technology partners, including AWS, Microsoft Azure, and Google Cloud, where relevant to client opportunities.
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• Participate in co-selling and joint go-to-market activities while maintaining direct ownership and accountability for sales results.
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• Leverage ecosystem relationships to accelerate opportunities, strengthen solution positioning, and expand enterprise relationships.
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• Represent CEI effectively in partner and customer-facing meetings, events, and strategic discussions.
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Internal Collaboration

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• Partner with CEI's architecture, engineering, presales, and delivery teams throughout the sales lifecycle to develop solutions that align with client requirements.
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• Collaborate with CEI account and sales teams to identify Databricks opportunities within existing enterprise relationships.
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• Provide Databricks-related sales expertise and opportunity support to the broader organization when needed.
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• Share customer and market feedback to strengthen solution positioning, sales enablement, and go-to-market execution.
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About Us : CEI or Computer Enterprises, Inc., is an AI engineering and transformation partner that designs, builds, and operationalizes production grade AI across enterprise systems. We help organizations move from ambition to execution by embedding AI into mission critical platforms, enterprise data environments, and operational workflows. CEI specializes in turning AI strategy into measurable outcomes through governed, scalable, cloud native solutions engineered for reliability, security, and adoption at scale. Our approach emphasizes enterprise grade integration, operational readiness, and responsible AI practices, ensuring initiatives deliver value beyond isolated pilots. By aligning AI engineering with business priorities, CEI enables organizations to modernize operations, accelerate decision making, and achieve sustained performance improvements across the enterprise. Our teams combine deep engineering expertise, industry experience, and change leadership to operationalize AI responsibly, securely, and durably across complex, regulated, multi-vendor enterprise technology environments worldwide. This drives measurable outcomes faster, reduces risk, and builds long-term enterprise value at scale globally sustainably.