Senior Sales Consultant - Data Products Team

CentralReach, a leading provider of autism and IDD care software for Applied Behavior Analysis (ABA), multidisciplinary therapy, and special education, trusted by over 200,000 users, is seeking a Senior Sales Consultant to own the technical side of every data opportunity.

The Data Products team, a startup within CentralReach, is establishing its own playbook and processes. They are looking for someone with low patience for heavy process and a high ownership mentality. You challenge weak requirements, kill poorly scoped evaluations early, and do not wait for a playbook to be handed to you. You will have meaningful influence over product direction and the data sales process.

Key Accountabilities:

• Own the technical portion of the sales process from discovery through technical validation and close
• Partner with Account Managers and new business Account Executives on account strategy, qualification, deal planning, and stakeholder management
• Work with the VP of Data Products to evaluate the existing customer base, identify which accounts are ready for which products, and help build target lists with Account Managers
• Lead technical discovery to uncover the customer’s architecture, workflows, pain points, decision criteria, and business objectives, then translate what you find into clear solution designs across Advanced BI, Data Warehouse, APIs, and Benchmarking
• Deliver tailored demos that connect capability to measurable customer outcomes rather than scripted product tours
• Scope and run proofs of concept and technical evaluations with success criteria defined up front, driving each to a yes or no on a timeline
• Build and defend the business case, including TCO and ROI comparisons against a customer building the capability in-house
• Map each customer to the right product for their current stage and name what they will need at the next stage
• Handle technical objections spanning architecture, security, data access, scalability, deployment, APIs, entitlements, and integration, and test what competitors actually deliver rather than absorbing what prospects believe they deliver
• Create reusable evaluation plans, ROI models, solution patterns, and technical collateral that let the broader sales organization participate
• Provide structured feedback to Product and Engineering from customer conversations, competitive evaluations, and recurring technical requirements, and support handoff after close so expectations, architecture decisions, and success criteria are documented
• Use AI tooling (LLMs, code copilots, semantic search) as a core part of your workflow. This is how the team works, not a nice-to-have

Desired Skills and Experience:

• 5+ years in sales engineering, solutions consulting, or pre-sales architecture supporting a technical B2B product in data infrastructure, analytics, developer tools, observability, or enterprise AI
• A track record of evaluations that ended in a decision rather than in an indefinite pilot, and of deals you can point to as technically won
• Experience selling to data and engineering leaders alongside business buyers such as CEOs, CFOs, and COOs
• Exceptional written and verbal communication, with the ability to explain complex methodology to a non-technical executive without losing precision
• Comfortable in a team still building its processes, with a bias toward action

Commercial Judgment:

• Willingness to disqualify and to challenge weak requirements before an evaluation gets scoped
• Understanding of how architecture and delivery decisions affect pricing, packaging, and renewal outcomes, including consumption-based models
• Sound instincts about where technical effort is worth spending across several live opportunities at once
• Low ego, with real curiosity about how customers work rather than about what the product does

Technical Skills:

• Working knowledge of modern data architecture: warehouses, databases, APIs, cloud infrastructure, and pipelines
• Understanding of data governance, de-identification, suppression, entitlements, and the audit requirements of externally facing analytics
• Enough architecture depth to hold a credible conversation with a head of data who has already stood up their own stack, without reaching for unnecessary complexity

Preferred Qualifications:

• Experience at a data, analytics, cloud, infrastructure, or observability company and familiarity with platforms such as Snowflake, Databricks, dbt, or Looker
• Experience with enterprise security review, procurement, and technical diligence
• Experience joining or helping build an early sales engineering organization or selling an emerging category where customer education is part of the cycle
• Healthcare data exposure such as claims, quality measures, or de-identification standards