4 days ago

Manager, Analytics Engineering Finance Data

Affirm

Hybrid
Full Time
$240,000
Hybrid

Job Overview

Job TitleManager, Analytics Engineering Finance Data
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$240,000
LocationHybrid

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Job Description

About Affirm

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

Role Overview: Manager, Analytics Engineering Finance Data

Our Financial Systems team is looking for a Manager, Analytics Engineering Finance Data to lead a team that turns complex finance data into reliable, governed, audit-ready reporting foundations. You will own end-to-end delivery of governed data models and the semantic layer that power reconciliations, close, and external reporting automation at Affirm. We're looking for someone who can lead, execute, and partner deeply across Accounting, Finance, and Data Engineering—operating as a hands-on technical leader to improve controls, data quality, and month-end outcomes at scale. The ideal candidate will deliver impact through scalable semantic layers and reporting solutions that elevate Finance function outcomes.

What You'll Do

  • Lead end-to-end delivery of finance data models that support reconciliations, journal entry preparation, and close workflows, with a focus on reliability, controls, and audit readiness.
  • Own the Financial Reporting semantic layer strategy and execution, including definition governance and adoption across reporting surfaces.
  • Drive migration and modernization of reconciliation and close-support reporting into standardized, automated outputs where appropriate.
  • Partner with Accounting and Finance stakeholders to translate close and audit requirements into durable data contracts, model specifications, and delivery roadmaps.
  • Build and evolve reporting data products that make financial insights easy to consume and hard to misinterpret, partnering with BI and Financial Reporting tools (for example Sigma and Workiva).
  • Build the foundations for AI-assisted finance analytics by enabling AI agents to safely access governed finance datasets (for example, through well-defined metrics, strong documentation, and permissioned datasets) to support self-service questions and reporting workflows.
  • Establish strong analytics engineering practices across the stack (testing, documentation and glossary stewardship, monitoring/alerting, code review, release discipline, and operational ownership).

What We Look For

  • Strong problem-solving and systems thinking: able to understand end-to-end accounting scenarios and translate them into well-structured data models that are clear, reliable, and easy to maintain.
  • Experience working in audit and controls-driven environments (for example SOX-relevant processes), with an understanding of how data quality, lineage, and evidence tie to financial reporting outcomes.
  • Ability to translate accounting and controls requirements into clear data contracts (inputs, transformations, definitions, ownership, and expected outputs) that can be implemented and operated reliably.
  • Self-starter and self-learner: takes ownership, ramps quickly in new domains, and prioritizes durable solutions over attachment to any specific tool or approach.
  • Strong experience delivering analytics engineering or data engineering initiatives end-to-end in a complex environment, including cross-functional alignment.
  • Ability to influence without authority across Accounting, Finance Systems, and Engineering to drive decisions, alignment, and delivery.
  • Proven ability to build reporting data products for business users (for example, curated datasets and governed metrics that power BI and external reporting workflows), partnering effectively with BI and financial reporting tooling teams.
  • Deep experience with modern data transformation and warehousing patterns (for example dbt and Snowflake), including production operations and reliability practices.

Compensation and Benefits

USA base pay range (CA, WA, NY, NJ, CT) per year: $215,000 - $265,000

USA base pay range (all other U.S. states) per year: $191,000 - $241,000

Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.

We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:

  • Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
  • Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
  • Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
  • ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount

Key skills/competency

  • Finance Data Modeling
  • Analytics Engineering
  • Data Governance
  • Financial Reporting
  • Audit Readiness
  • SOX Compliance
  • dbt
  • Snowflake
  • BI Tools (Sigma, Workiva)
  • Cross-functional Leadership

Tags:

Analytics Engineering Manager
finance data
data models
reporting
reconciliation
audit
controls
data quality
semantic layer
AI analytics
stakeholder management
dbt
Snowflake
Sigma
Workiva
BI tools
data warehousing
data transformation
SQL
ETL

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How to Get Hired at Affirm

  • Research Affirm's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
  • Tailor your resume for analytics engineering: Highlight experience in finance data modeling, SOX compliance, and modern data stack tools like dbt and Snowflake.
  • Showcase leadership and influence: Prepare examples demonstrating your ability to lead technical initiatives and align diverse stakeholders (Accounting, Finance, Engineering).
  • Prepare for technical depth: Be ready to discuss your experience with data governance, audit readiness, and building scalable reporting solutions.
  • Demonstrate problem-solving: Practice articulating how you translate complex accounting scenarios into reliable data models and drive data quality.

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