Job Overview
Location
New York City
Job Type
Full-time
Category
Sales
Date Posted
May 21, 2026
Full Job Description
đź“‹ Description
- • Own the full enterprise sales cycle for Preql, from initial discovery through implementation and early customer expansion, with primary focus on financial services clients
- • Conduct tailored discovery sessions and product demos aligned with customers’ actual workflows, priorities, and pain points around data governance and AI adoption
- • Build and scope Proof of Concept (POC) environments directly within Preql’s platform to demonstrate value in real-world financial data contexts
- • Lead technical conversations with data engineers, analysts, and IT teams to address architecture, integration, and data pipeline concerns
- • Engage business stakeholders including CFOs, FP&A leaders, and finance operations teams to align Preql’s capabilities with budgeting, forecasting, and reporting objectives
- • Build and nurture relationships across the entire buying committee—not just single champions—to drive consensus and accelerate decision-making
- • Execute end-to-end deal closure activities including security reviews, procurement workflows, contract negotiation, forecasting, and implementation planning
- • Remain actively involved through customer launch and early expansion phases to ensure adoption success and identify upsell opportunities
- • Provide direct product and market feedback to the founding team based on customer interactions, pain points, and competitive insights
- • Help shape and refine Preql’s GTM strategy, sales playbook, and messaging for future hires by documenting successful patterns and refining outreach approaches
- • Represent Preql in high-stakes enterprise environments where data accuracy, compliance, and AI reliability are critical to operational outcomes
- • Navigate complex organizational structures common in financial services firms to identify key decision-makers and influence multi-team evaluations
- • Communicate credibly about AI’s practical applications in enterprise settings, distinguishing modern AI systems from legacy automation tools
- • Operate autonomously in a fast-paced, ambiguous startup environment with minimal bureaucracy and high expectations for ownership and initiative
- • Collaborate directly with founders to prioritize pipeline, refine targeting, and evolve the company’s market positioning based on real-world customer feedback
- • Translate technical product capabilities into business value propositions for non-technical finance leaders without oversimplifying or misrepresenting functionality
- • Maintain deep awareness of financial data workflows including reconciliation, allocations, general ledger structures, and FP&A tooling to contextualize Preql’s value
🎯 Requirements
- • 5+ years in sales, solutions engineering, and/or as a data practitioner within financial services
- • Experience selling into enterprise organizations
- • Experience in financial services and/or finance orgs, and deep familiarity with their unique data challenges
- • Ability to communicate effectively with both technical and business stakeholders
- • Comfortable working directly with founders and operating without a lot of structure
- • Strong written and verbal communication skills
🏖️ Benefits
- • Opportunity to be the first GTM hire and shape the sales motion for a high-potential startup
- • Direct influence on company strategy and product direction through customer feedback
- • Collaborative, low-bureaucracy environment with ownership over outcomes
- • Exposure to cutting-edge AI and data infrastructure challenges in enterprise settings
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Preql Inc.
Preql Inc. provides a no-code business-intelligence platform that lets non-technical users define metrics, build reports, and schedule data refreshes directly on cloud warehouses. The software connects to Snowflake, BigQuery, Redshift, and Postgres, translating plain-English inputs into version-controlled SQL and automatically generating semantic data models. Teams collaborate inside a web interface to govern definitions, validate logic, and embed live dashboards without writing code or maintaining separate ETL pipelines. Founded in 2020 and headquartered in New York City, the company targets operations, finance, and growth teams seeking self-service analytics while keeping governance and security centralized.
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