VP Sales - Data Management & Data Analytics

• Base salary ranges: $220k - $250k
• Total compensation includes base salary, sales rewards & commission plan, and RSU's
• Location - This is a fully remote role. Applicants must be based in the mainland U.S with travel required up to 70%
• To learn more about EXL and what we offer, please visit us at https://www.exlservice.com/us-careers-and-benefits

Vice President, Sales - Data Management and Data Analytics

Individual Contributor| New Logo Hunter | US Territory | Base + Commission | Remote / Travel Required

***This is an individual contributor role with high visibility in the organization - Candidates with an entrepreneurial mindset and experience in Data & Analytics Sales will be a good fit for this role. ***

ABOUT EXL

EXL (NASDAQ: EXLS) is a global data analytics and digital operations company. For 25 years, we have helped the world's leading enterprises turn complex data into intelligent action - combining deep domain expertise, AI, advanced analytics, and business process excellence to deliver measurable outcomes at scale.

EXL's Technology & Digital practice works with companies across the full technology spectrum - software, SaaS, semiconductor, hardware, internet platforms, cybersecurity, gaming, fintech, edtech, logistics technology, and telecommunications - helping them scale operations, improve unit economics, and embed analytics and AI into the fabric of how they work.

EXL is not an IT company.

We do not sell infrastructure, networking, or managed IT services. We sell operations transformation, data and AI services, and analytics - backed by proprietary technology, offshore delivery excellence, and a 90% AI implementation success rate against an industry average where nearly 70% of enterprise AI initiatives fail.

What you will lead

• Pipeline development and maturation with alliance partners
• Scaling go-to-market initiatives across industry and alliance teams
• Qualifying and advancing consulting opportunities as part of a broader GTM team

Sales execution

• Run a disciplined sales pipeline covering lead management, qualification, and consistent application of established sales methodology
• Identify and align the right Data Management resources to pursue, win, and manage opportunities
• Build organized, differentiated go-to-market activities
• Develop overview materials that carry initial meetings and conversations
• Lead preparation for formal sales meetings and orals on qualified opportunities
• Shape pursuits by drawing on relationships for insight and influence setting win themes, aligning messaging to client priorities, guiding proposal and orals materials, and presenting in orals sessions where appropriate
• Support pre-sales with deep product knowledge, demonstrations tailored to the client's environment, and industry expertise that informs bespoke solutions

Market offering and planning support

• Support the development and positioning of Data Management market offerings
• Support leadership in building account and GTM plans through the annual planning cycle
• Participate in industry leadership calls and in-person meetings, including planning and preparation

The successful candidate will

• Work independently and contribute effectively as part of a team
• Communicate clearly in writing and in person, including with senior client stakeholders
• Build and sustain professional relationships across clients, partners, and internal teams
• Lead projects and workstreams from start to finish
• Manage and prioritize competing demands in a fast-paced environment and consistently meet deadlines
• Hold a high bar for detail and quality of work product
• Mentor others and provide clear guidance

Qualifications Required:

• 10+ years selling data and AI services or offerings built on at least one major public cloud or data platform (Amazon Web Services, Google Cloud Platform, Microsoft Azure, Databricks, Snowflake)
• Track record managing complex clients with long sales cycles and significant transaction values, with emphasis on data platforms (cloud native such as ADLS and Fabric, cloud enabled such as Databricks and Snowflake), ETL, and data visualization tools
• Working understanding of cloud solution architecture, including scalable, available, and fault-tolerant designs and integration across cloud applications and cloud types (public, private, hybrid), sufficient to position solutions credibly and shape them alongside technical teams.
• Experience selling Generative AI services, with enough command of the landscape to hold a credible conversation on the GenAI platforms clients are standardizing on (Amazon Bedrock, Azure OpenAI and AI Foundry, Google Vertex AI, Databricks Mosaic AI), the patterns that carry enterprise use cases (RAG, fine-tuning, multi-agent and agentic workflows, model orchestration), and the unstructured data readiness and governance work all of it depends on
• Grounding in traditional machine learning and MLOps (SageMaker, Azure ML, Vertex AI, Databricks ML), enough to steer clients toward the right approach rather than defaulting to a language model
• Ability to build the business case for Data and AI investments with business and technical buyers, including where value is realistic and where it is not
• Familiarity with migrating complex, multi-tier solutions to cloud platforms and with the modern delivery methodologies and frameworks used to do it
• Ability to travel up to 50% on average, depending on the work you do and the clients and sectors you serve
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

Preferred

• Experience in the diversified industries that include Manufacturing, Retail, ecommerce, big tech, energy/utilities, infrastructure.
• Experience positioning data monetization or externally facing data products, not only internal modernization
• Familiarity with data mesh and data product operating models, and with the organizational change that comes with them
• Experience selling generative AI or agentic AI engagements that reached production rather than stopping at pilot
• Familiarity with AI governance and responsible AI requirements as they come up in enterprise procurement
• Partner sales certifications or accreditations from a hyperscale or data platform vendor

The posted base salary range is the hiring base salary range for this role. Final offers are based on several factors, including: the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position.