Revenue Analytics Engineer — Remote, AI-Driven Data

Affirm; Kitchener; On-site; CAD 241,000 - 325,000; Full time

Benefits offered by this job

Health care coverage

Flexible Spending Wallets

Time off

ESPP

Job summary

Affirm is seeking an experienced Analytics Engineer to lead the development of scalable, trusted data products for our Revenue teams. You will turn ambiguous problems into durable solutions across data modeling, metrics, dashboards, automation, governance, and AI enablement.

You will set the technical direction for Revenue's data layer, establish semantic foundations for AI, and raise data quality and impact across the Revenue organization.

Qualifications

• 7+ years in analytics engineering, BI, data engineering or related technical analytics role.
• Deep expertise in SQL, dbt, data modeling, metrics design, data quality, documentation.
• Experience with modern analytics engineering practices and AI enablement in analytics workflows.

Responsibilities

• Lead high-impact data product initiatives for Revenue, from problem definition through design, rollout and adoption.
• Advance AI initiatives within the Revenue data ecosystem by identifying use cases and establishing semantic, metadata, and quality foundations.
• Design and build durable data products powering revenue operations, reporting, and self-service analytics.
• Set technical direction for Revenue’s data layer, including dbt models, metrics, semantic structures, lineage and governance.
• Identify opportunities to simplify, automate, and scale Revenue Analytics through improved data architecture and tooling.
• Provide technical leadership and mentorship to analysts and cross-functional partners.

Skills

Analytics engineering

SQL

Data modeling

Metrics design

Data quality

Documentation

AI enablement

Tools

Sigma

Looker

Tableau

Snowflake

Databricks

Job description

Affirm is seeking an experienced Analytics Engineer to lead the development of scalable, trusted data products for our Revenue teams. You will turn ambiguous problems into durable solutions across data modeling, metrics, dashboards, automation, governance, and AI enablement.

You will set the technical direction for Revenue's data layer, establish semantic foundations for AI, and raise data quality and impact across the Revenue organization.