Staff Analytics Engineer, Subledger Platform

This is a fully remote position, open to applicants in California, +4 more states.

📋 Description

• Develop and oversee dbt models for the financial subledger platform (staging → intermediate → canonical facts/balances/marts → semantic), which includes establishing naming conventions, macros, and reusable patterns.

• Establish robust data quality and controls in dbt: tests (unit/relationship/assertions), freshness checks, anomaly detection, and automated reconciliations that ensure close and audit preparedness.

• Integrate AI-assisted reconciliation features into the platform (within suitable security/control frameworks): automate variance analysis, identify probable root causes, and create human-readable reconciliation narratives and evidence artifacts.

• Manage end-to-end subledger data products (e.g., event/fact layers, balance rollforwards, reconciliation outputs) ensuring traceability from source events through transformations to reporting outputs.

• Collaborate with Accounting/Financial Reporting to convert requirements into clear model specifications (definitions, posting logic assumptions, tie-out rules) and deliver them as long-lasting dbt assets.

• Take charge of operational management in production: monitoring/alerting, incident handling, root-cause resolution, and maintaining release hygiene for the pipelines and models under your purview.

• Work with upstream engineering teams to define inputs and enhance source data quality through contracts and change management.

• Mentor and develop one Analytics Engineer (Poland) through code reviews, collaborative work, defined ownership, and clear technical guidance.

⛳️ Requirements

• Extensive, hands-on experience in analytics engineering: you have created and maintained production dbt projects (models, tests, macros, documentation, CI) and can manage them from start to finish.

• Proficient SQL and data modeling capabilities; experience in constructing canonical datasets that facilitate finance reporting, reconciliations, or other critical correctness outcomes.

• Background in managing data pipelines in a warehouse setting (Snowflake preferred): performance optimization, cost awareness, and reliability practices.

• Strong programming skills (Python preferred) for developing data tools and automation (e.g., control checks, reconciliation workflows, utilities, CLIs, and integrations).

• In-depth technical knowledge of Snowflake: architecture patterns (micro-partitioning/clustering, query optimization), security/governance (RBAC, masking policies), and operational excellence (monitoring, cost management, reliability).

• Strong sense of ownership and the ability to navigate ambiguous tasks through influence across Finance, Accounting, and Engineering teams.

• Nice to have:

• Familiarity with accounting principles (subledgers, journal entries/posting logic, balance rollforwards, tie-outs, close processes).

• Experience designing SOX-compliant controls and generating repeatable evidence from data pipelines.

• Experience utilizing AI/LLMs in data quality or reconciliation processes (e.g., anomaly explanation, automated investigation summaries), with a strong emphasis on governance and human-in-the-loop review.

• AWS experience (preferred): S3/IAM, data platform fundamentals, and cloud architecture concepts that facilitate secure, reliable data products.

🏝️ Benefits

• Comprehensive health care coverage - Affirm pays all premiums for all coverage levels for you and your dependents.

• Flexible Spending Wallets - generous stipends for expenditures on Technology, Food, various Lifestyle needs, and family planning expenses.

• Time off - competitive vacation and holiday policies allowing you to take time off to relax and rejuvenate.

• ESPP - An employee stock purchase plan that enables you to acquire shares of Affirm at a discounted rate.