Revenue Analytics Engineer - AI Data Products

Affirm; Houston (TX); On-site; USD 195,000 - 255,000; Full time

Benefits offered by this job

Remote-friendly

Competitive benefits

Paid time off

Job summary

Affirm is seeking an experienced analytics engineer to join the Revenue Analytics team. You will develop scalable data products supporting revenue operations, reporting, and AI enablement across data modeling, metrics, and governance.

You will set technical direction for the Revenue data layer, build durable data products, and mentor analysts while collaborating with cross-functional partners to improve data quality and impact.

Qualifications

• 7+ years of experience in analytics engineering, business intelligence, data engineering, or a related technical analytics role.
• Expertise in SQL, dbt, data modeling, metrics design, data quality, documentation, and modern analytics practices.
• Strong knowledge of BI tools and cloud data warehouses.

Responsibilities

• Lead high-impact data product initiatives for Revenue from design through rollout and adoption.
• Advance AI initiatives within the Revenue data ecosystem and establish semantic, metadata, and evaluation foundations.
• Design and build durable, well-tested data products powering revenue operations and executive reporting.
• Set technical direction for Revenue's data layer across dbt models, metrics, semantic structures, and governance.
• Identify opportunities to simplify and scale Revenue Analytics through improved data architecture and tooling.
• Provide technical leadership and mentorship to analysts and cross-functional partners.

Skills

SQL

dbt

data modeling

metrics design

data quality

documentation

analytics engineering practices

Tools

Sigma

Looker

Tableau

Snowflake

Databricks

Job description

Affirm is seeking an experienced analytics engineer to join the Revenue Analytics team. You will develop scalable data products supporting revenue operations, reporting, and AI enablement across data modeling, metrics, and governance.

You will set technical direction for the Revenue data layer, build durable data products, and mentor analysts while collaborating with cross-functional partners to improve data quality and impact.