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About Datavations
Datavations is a leading New York-based data and AI software specializing in the $2.3 trillion dollar building materials industry. Datavations gives building materials and home improvement manufacturers real-time, store-level visibility into pricing, assortment, and inventory across major retailers, including Home Depot, Lowe’s, and Menards. Manufacturers use this data to make sharper decisions about pricing, distribution, and how they show up on the shelf.
Our values
Customer Obsession : We are integrated in the industry with a customer-first obsession.
Proactive Ownership : We have agency for our actions and embody an entrepreneurial mindset.
Bias for Action : We maintain momentum with a can-do attitude; we value progress over perfection.
Eager to Grow : We stay curious and hungry to learn, viewing every failure with humility as an opportunity to grow.
Foster Collaboration : We work across boundaries with quiet competence, welcoming diverse perspectives and offering help unselfishly.
The Role
As a Sales Engineer, you’ll partner with Account Executives throughout the sales cycle — from the first technical conversation through close. You’ll validate our data against a prospect’s own numbers, build the analysis that makes our value obvious, and present and defend that analysis directly to technical and executive audiences. This is a hands-on, technical role at the center of the sales process, not a supporting one.
Core Responsibilities
Analysis & insight development: turn raw data into a clear, structured analysis tied to the specific business decision your audience is trying to make.
Deal scoping: scope technical requirements and build supporting pricing or proposal materials, surfacing feasibility issues early in the sales cycle.
Demo & presentation delivery: build and deliver product demonstrations and analytical presentations, including to senior and executive audiences, and adapt in real time when your findings are challenged.
Data validation: run correlation and variance analysis to validate our data against a prospect’s own data, and explain your methodology clearly to both technical and non-technical audiences.
Cross-functional handoff: work closely with sales, customer success, and product teams, including a clean handoff of documentation once a deal closes.
Tools & data fluency: work fluently with data and analytics tools (spreadsheets, SQL or similar, BI/reporting tools, Claude), and pick up new tools quickly, including AI-assisted workflows.
Core Skills & Experience
3+ years in a technical, pre-sales, or solutions-consulting role — sales engineering, solutions consulting, technical account management, or a similarly analytical customer-facing role.
Strong quantitative and analytical skills: comfortable working directly with data (spreadsheets, SQL or similar query languages, BI/reporting tools) and able to catch an error before it reaches a customer (ie - strong attention to detail).
Strong presentation and communication skills, with experience adapting technical material for different audiences, including senior stakeholders.
Nice to Have
Experience with retail or CPG point-of-sale, syndicated, or panel data.
Impact at Scale : Influence a $2.3 trillion industry by shaping how data science accelerates ROI for major manufacturers.
Autonomy & Growth : Enjoy the freedom to experiment with new technologies and see your ideas realized in production.
Collaborative Culture : Work alongside a supportive team that values positivity, proactive ownership, and continuous learning.
Professional Development : Work with Terraform, OpenTelemetry, GenAI coding tools, and modern
Compensation
The average range for this role is $110,000 - $130,000 depending on experience, skills, and alignment with the role’s responsibilities. This range reflects our current national expectations for qualified candidates. Exceptional candidates based in our NYC office may be considered for a higher range. Total compensation may also include equity, performance bonuses, and a comprehensive benefits package.
We’re committed to paying competitively and equitably, and we regularly review our compensation structures to ensure they align with the market and support our values Originally posted on Himalayas