Staff Analytics Engineer, Subledger Platform

About This RoleAI processing…

Key Responsibilities

• 1
  Build and own dbt models for the financial subledger platform (staging → intermediate → canonical facts/balances/marts → semantic), including naming conventions, macros, and reusable patterns.
• 2
  Implement strong data quality and controls in dbt: tests (unit/relationship/assertions), freshness, anomaly checks, and automated reconciliations that support close and audit readiness.
• 3
  Embed AI-assisted reconciliation capabilities into the platform (within appropriate security/controls guardrails): automate variance triage, suggest likely root causes, and generate human-reviewable reconciliation narratives and evidence artifacts.
• 4
  Own end-to-end subledger data products (e.g., event/fact layers, balance rollforwards, reconciliation outputs) with traceability from source events through transformations to reporting outputs.
• 5
  Partner with Accounting/Financial Reporting to translate requirements into clear model specifications (definitions, posting logic assumptions, tie-out rules) and ship them as durable dbt assets.
• 6
  Drive production operational ownership : monitoring/alerting, incident response, root-cause fixes, and release hygiene for the pipelines and models you own.
• 7
  Collaborate with upstream engineering teams to define inputs and improve source data quality via contracts and change management.
• 8
  Coach and develop one Analytics Engineer (Poland) via code review, pairing, scoped ownership, and clear technical direction.

Requirements

• Deep, hands-on analytics engineering experience: you have built and maintained production dbt projects (models, tests, macros, documentation, CI) and can own them end-to-end.
• Deep Snowflake technical expertise: architecture patterns (micro-partitioning/clustering, query optimization), security/governance (RBAC, masking policies), and operational excellence (monitoring, cost management, reliability).
• Nice to have: Experience with accounting concepts (subledgers, journal entries/posting logic, balance rollforwards, tie-outs, close processes).
• What we look for Deep, hands-on analytics engineering experience: you have built and maintained production dbt projects (models, tests, macros, documentation, CI) and can own them end-to-end.
• Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office.
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Perks & Benefits