Note: The job is a remote job and is open to candidates in USA. Preql AI helps enterprises clean, unify, and govern messy internal data for AI, analytics, and reporting. The Forward Deployed Engineer will work closely with finance organizations to build semantic models and ensure accurate data integration, while also providing valuable feedback to the engineering team.
Responsibilities
- The business outcomes for a portfolio of enterprise accounts, from kickoff through production and expansion
- Semantic models for finance logic: revenue recognition, cost allocation, GL and cost center hierarchies, headcount and driver based planning
- Source integration and mapping across ERPs, planning systems, and warehouses, including the reconciliation problems that surface once real data lands
- Working sessions with controllers, FP&A leads, and customer data teams, translating between finance language and data models
- The judgment call on what is a modeling problem, a source data problem, or a product gap, and routing each one to the right place
- A steady stream of product feedback backed by specifics, not anecdotes, so engineering builds against real customer friction
- Reusable models, templates, and documentation that shrink time to value on every subsequent account
Skills
- 5+ years building with data in production, with deep SQL fluency and comfort in Python
- Direct experience with cloud warehouses (Snowflake, Databricks, BigQuery) and transformation tooling (dbt or equivalent)
- Real working knowledge of financial data. You know why the finance team's definition of revenue is different from the data team's, and you have modeled a chart of accounts, an allocation, or a close process before
- Experience working directly with enterprise customers, including the parts that are uncomfortable: scoping, pushing back, and delivering bad news early
- High tolerance for ambiguity. Early accounts will not have a playbook, and you will write the playbook
- Judgment about when to solve something for one customer and when to solve it for all of them
- Familiarity with ERP and planning systems (NetSuite, Workday, SAP, Oracle)
- Background in consulting, solutions architecture, or professional services at a data or AI company
- You have worked with regulated buyers
- You have been the first or second technical hire on a customer facing team
- Time spent inside a finance or accounting function, or close enough to one to have felt a close
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