Revenue Analytics Engineer: Data Products & AI

Affirm; Halifax; On-site; CAD 173,000 - 233,000; Full time

Benefits offered by this job

Health coverage

Flexible Spending Wallets

Vacation and holidays

ESPP

Job summary

Affirm is seeking an experienced analytics engineer to join the Revenue Analytics team. You will develop scalable data products, set technical direction for the revenue data layer, and enable AI across analytics workflows.

You’ll lead ambiguous problems to durable solutions, mentor analysts, and collaborate with stakeholders to improve data quality and governance across the Revenue organization.

Qualifications

• 7+ years of analytics engineering or related technical analytics role.
• Deep expertise in SQL, dbt, data modeling, metrics design, data quality, and docs.
• Strong knowledge of BI tools (Sigma/Looker/Tableau) and cloud data warehouses (Snowflake).
• Understanding of AI foundations: semantic layers, metadata, lineage, and data governance.

Responsibilities

• Lead high-impact data product initiatives for Revenue from problem definition to rollout.
• Advance AI initiatives within the Revenue data ecosystem and establish semantic foundations.
• Design and build durable, well-tested data products powering revenue reporting and analytics.
• Set technical direction for Revenue’s data layer across dbt models, metrics, and documentation.
• Identify opportunities to automate and scale Revenue Analytics via 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

Looker

Sigma

Tableau

Snowflake

Databricks

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, set technical direction for the revenue data layer, and enable AI across analytics workflows.

You’ll lead ambiguous problems to durable solutions, mentor analysts, and collaborate with stakeholders to improve data quality and governance across the Revenue organization.