Staff Analytics Engineer, Subledger Platform

This is a fully remote position, open to applicants in Canada.

📋 Description

• Develop and manage dbt models for the financial subledger platform, encompassing staging, intermediate, canonical facts, balances, marts, and semantic layers, while adhering to naming conventions, macros, and reusable patterns.

• Establish robust data quality measures and controls in dbt, including tests (unit, relationship, assertions), freshness checks, anomaly detection, and automated reconciliations to ensure readiness for closing and auditing processes.

• Integrate AI-assisted reconciliation functionalities into the platform, ensuring compliance with appropriate security and control frameworks: automate variance investigations, identify probable root causes, and create human-reviewable narratives and evidence artifacts for reconciliation.

• Manage all aspects of subledger data products, such as event and fact layers, balance rollforwards, and reconciliation outputs, ensuring traceability from source events through transformations to final reporting outputs.

• Collaborate with Accounting and Financial Reporting teams to transform requirements into precise model specifications, including definitions, posting logic assumptions, and tie-out rules, delivering them as robust dbt assets.

• Take responsibility for production operational management, including monitoring and alerting, incident response, root-cause analysis, and release hygiene for your pipelines and models.

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

• Mentor and develop one Analytics Engineer based in Poland through code reviews, collaborative work, scoped responsibilities, and clear technical guidance.

⛳️ Requirements

• Extensive, hands-on experience in analytics engineering: you have designed and maintained production dbt projects, including models, tests, macros, and documentation, taking full ownership of them.

• Proficient SQL and data modeling capabilities; experience in creating canonical datasets that facilitate financial reporting, reconciliations, or other outcomes critical to accuracy.

• Experience managing data pipelines within a warehouse setting (preferably Snowflake): performance optimization, cost awareness, and reliability practices are essential.

• Strong programming proficiency (preferably in Python) for developing data tools and automation, including control checks, reconciliation workflows, utilities, CLIs, and integrations.

• In-depth technical knowledge of Snowflake, including architectural patterns (micro-partitioning, clustering, query optimization), security and governance (RBAC, masking policies), and operational best practices (monitoring, cost management, reliability).

• A strong sense of ownership and the ability to navigate ambiguous tasks through influence across Finance, Accounting, and Engineering stakeholders.

• Nice to have:

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

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

• Knowledge of applying AI and LLMs to data quality or reconciliation processes, including anomaly explanations and automated investigation summaries, with strong governance and human-in-the-loop reviews.

• AWS experience is a plus, including S3/IAM, data platform fundamentals, and cloud architecture concepts that support secure and 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 expenses related to Technology, Food, various Lifestyle needs, and family formation.

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

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