Forward Deployed Engineer, Finance Solutions

🕒 August 10

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

💸 Financial Planning and Analysis (FP&A)

👻 Ghost score 19%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Preql AI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2022

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

Artificial Intelligence • SaaS • Enterprise

Preql AI is an enterprise-focused AI data platform that automates the hardest parts of AI adoption by cleaning, reconciling, and contextualizing messy data across ERP, CRM, HR, and expense systems. Using agentic semantic modeling and continuous data-cleaning agents, it creates auditable, AI-ready pipelines and structured outputs for copilots, dashboards, and decision workflows, with enterprise-grade security, governance, and quick integrations for finance, operations, and technology teams.

📋 Description

• Own business outcomes for a portfolio of enterprise accounts from kickoff through production and expansion • Build semantic models for finance logic, including revenue recognition, cost allocation, GL and cost center hierarchies, headcount, and driver-based planning • Integrate and map sources across ERPs, planning systems, and warehouses, including reconciliation of real data • Conduct working sessions with controllers, FP&A leads, and customer data teams • Determine whether issues are modeling problems, source data problems, or product gaps, and route them appropriately • Provide specific product feedback based on customer friction • Create reusable models, templates, and documentation to reduce time to value • Take accounts from installation to trusted first output and explain reporting numbers back to their source • Improve delivery playbooks and support expansion conversations and onboarding of future engineers

🎯 Requirements

• 5+ years building with data in production • Deep SQL fluency and comfort in Python • Direct experience with Snowflake, Databricks, or BigQuery • Experience with dbt or equivalent transformation tooling • Working knowledge of financial data, including chart of accounts, allocations, or close processes • Experience working directly with enterprise customers, including scoping, pushing back, and delivering bad news early • High tolerance for ambiguity and ability to create processes without an existing playbook • Judgment about when to build a customer-specific solution versus a reusable solution • Familiarity with ERP and planning systems such as NetSuite, Workday, SAP, or Oracle • Background in consulting, solutions architecture, or professional services at a data or AI company is a strong signal • Experience with regulated buyers is a strong signal • Experience as the first or second technical hire on a customer-facing team is a strong signal • Experience inside a finance or accounting function, or equivalent exposure to finance close processes, is a strong signal