Analytics Engineer / BI Data Modeler

We’re looking for an experienced Analytics Engineer (or BI Data Modeler) to build a business-trusted analytics layer on top of our production data. Our core system runs on PostgreSQL (application stack: NestJS + TypeORM) and integrates with QuickBooks and Salesforce. The operational schema is optimized for transactions (OLTP); your mission is to turn it into clear analytical models, consistent metrics, and reliable historical logic that power reporting and decision-making. What you’ll do Translate operational data into business concepts (e.g., Orders, Invoices, Bills, Payments, Customers, Warehouses, Revenue, Margin etc). Design analytics-friendly models (facts/dimensions, star schemas where appropriate) with clear grain, keys, and definitions. Build aggregated and denormalized tables/views optimized for BI consumption (Metabase, Power BI, Looker, etc.). Implement a semantic / metrics layer using Cube.dev (definitions, reusable measures, dimensions, and business logic). Standardize core metrics (revenue, margin, aging, win rate, quote time, fulfillment KPIs) with documentation and alignment across teams. Model status/history and event-based logic accurately (paid/voided/overdue/cancelled/re-quoted, lifecycle timestamps, effective-dated changes). Reconcile and unify data across systems (application, QuickBooks, Salesforce) into canonical business models. Partner with engineering and business stakeholders to ensure models reflect real workflows and become the company’s source of truth. What we’re looking for Strong SQL and PostgreSQL skills (performance-aware modeling, window functions, incremental patterns, etc.). Proven experience building analytics data models (fact/dimension design, star schema, metric layers / semantic layers). Track record converting OLTP schemas into analytics-ready structures. Solid understanding of financial/operational data (invoicing, payments, AR/AP, terms, due dates, aging). Comfort working with complex business rules and turning them into consistent, testable definitions. Nice to have Experience with dbt (or similar transformation frameworks). Hands-on experience with Cube.dev (semantic layers, metrics definitions, governance). Experience with Metabase / Looker / Power BI. Experience with snapshot/event-driven modeling (SCD, audit trails, lifecycle modeling). Domain background in logistics, marketplaces, or operational SaaS. What this role is not Not a “dashboard-only” BI role. Not purely data infrastructure / platform engineering. The focus is on business-correct, durable data models and metrics that the whole company can rely on. Job Type: Full-time Pay: $65,000.00 - $72,000.00 per year Benefits: 401(k) Dental insurance Health insurance Paid time off Vision insurance Work Location: In person