Senior / Staff Analytics Engineer

🕒 Yesterday

🇺🇸 United States – Remote

💵 $140k - $160k / year

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

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Fora Financial

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2008

💸 Finance

💳 Fintech

🤝 B2B

Finance • Fintech • B2B

Fora Financial is a business financing company that provides fast, flexible capital solutions to small and mid-sized businesses. Since 2008 it has offered products including small business loans, revenue advances, lines of credit, SBA loans, term loans, and equipment financing, with funding amounts up to $1. 5 million and expedited approval and funding timelines. Fora partners with banks and third-party funding providers to underwrite and deliver working capital across industries such as construction, manufacturing, retail, medical, and restaurants, emphasizing relationship-driven service and credit-access for businesses with varied credit profiles.

📋 Description

• dbt at Fora: project structure, conventions, CI/CD, tests, contracts, documentation, and performance. • Data models across bronze, silver, and gold layers. • The semantic layer (dbt MetricFlow or equivalent): metric definitions, dimensions, governance, and adoption. • Production operation of the transformation layer: jobs, dependencies, failures, retries, alerts, environments, and release hygiene. • Python tooling for validation, dbt utilities, lightweight automation, and integrations. • Data quality, test coverage, and observability for modeled tables. • Partnership with Risk & Analytics to formalize business metrics currently spread across SQL, Tableau, and analyst knowledge.

🎯 Requirements

• Deep dbt experience. You have shipped and operated dbt as production software, not just a SQL wrapper. You have opinions about structure, macros, packages, tests, contracts, and CI. • Strong dimensional and event-based modeling fundamentals: star schemas, conformed dimensions, slowly changing dimensions, point-in-time logic, grain discipline, and event-based modeling. • Semantic-layer experience. You have built or owned metric definitions as code using MetricFlow, LookML, Cube, AtScale, or similar. • Python competence for production analytics: API pulls, validation scripts, data quality checks, dbt utilities, lightweight automation, and debugging. You do not need to be a platform engineer, but you cannot be SQL-only. • Working knowledge of orchestration: DAGs, dependencies, retries, alerts, incremental processing, logs, SLAs, and deployment environments. • Git fluency: branches, rebases, conflict resolution, and meaningful commit history. • Clear stakeholder communication. You can explain trade-offs, say no diplomatically, and maintain standards while building trust. • Strong writing. You write useful PRs, durable documentation, and decision records other people can follow. • AI-native curiosity. You are actively learning how LLMs, MCP, and governed semantic layers change analytics workflows, and you want to apply that learning responsibly. • 3+ years of analytics engineering experience for Senior; 6+ for Staff. Level is based on scope of ownership, technical judgment, and ability to set direction independently.

🏖️ Benefits

• Company-subsidized medical, dental, and vision plans with leading insurance providers. • 401(k) plan with company match. • Life insurance at no cost to employees. • Generous time off plan, including rollover vacation days. • Health care and dependent care flexible spending accounts. • Commuter benefits. • Remote working model.