2 months ago
Remote, United StatesSenior
Responsibilities
- Own business outcomes for a portfolio of enterprise accounts from kickoff through production and expansion.
- Build semantic models for revenue recognition, cost allocation, general-ledger and cost-center hierarchies, headcount, and driver-based planning.
- Integrate and map sources across ERP systems, planning systems, and data warehouses, including reconciliation of real customer data.
- Lead working sessions with controllers, FP&A leads, and customer data teams to translate finance requirements into data models.
- Determine whether issues are modeling problems, source-data problems, or product gaps and route them appropriately.
- Provide specific product feedback based on customer friction so engineering can build effective solutions.
- Create reusable models, templates, and documentation that reduce time to value for future accounts.
- Explain customer reporting numbers back to their sources and deliver trusted outputs in production.
Requirements
- At least 5 years of production data-building experience with deep SQL fluency and comfort in Python.
- Direct experience with Snowflake, Databricks, or BigQuery and transformation tooling such as dbt or an equivalent.
- Working knowledge of financial data, including chart-of-accounts modeling, allocations, revenue definitions, or close processes.
- Experience working directly with enterprise customers, including scoping, pushing back, and communicating difficult news early.
- Ability to operate with ambiguity, exercise judgment about customer-specific versus reusable solutions, and create delivery playbooks.
- Familiarity with NetSuite, Workday, SAP, or Oracle is a strong signal.
- Background in consulting, solutions architecture, or professional services at a data or AI company is a strong signal.
- Experience with regulated buyers, being an early technical hire on a customer-facing team, or working in finance or accounting is a strong signal.
About Preql AI
Preql builds an AI-powered data platform for finance teams that unifies financial and operational data, automates reconciliation, and delivers reliable reporting without heavy engineering. Its product provides no-code, agentic workflows to clean, transform, centralize data, and maintain a shared metric catalog. Founded in 2022 and headquartered in New York, this privately held company serves enterprises seeking to streamline profitability and performance analysis across teams, products, and markets.