Remote Revenue Analytics Engineer II — Data Products

Affirm; Polska; Hybrid; PLN 180,000 - 300,000; Full time

Benefits offered by this job

Equity from parent company

Lux Med healthcare

MultiSport card

Learning & development programs

Family healthcare support

Lyra mental well-being sessions

Northstar financial planning tools

Employee Resource Groups

Tax benefits eligibility

Job summary

Affirm is seeking an Analytics Engineer II, Full Stack in Revenue Analytics. This remote-from-Poland role focuses on building scalable data products, semantic layers, and governance to support AI-enabled revenue decisions. You’ll own data modeling, metrics, dashboards, and automation end-to-end.

The role requires 3+ years in analytics engineering or BI, with strong SQL, dbt, Python, and data visualization. Collaboration across data, engineering, and business stakeholders is essential.

Qualifications

• 3+ years in analytics engineering or BI
• Strong SQL, dbt, Python, data modeling
• Experience with BI tools and cloud warehouses
• Knowledge of AI data foundations and governance

Responsibilities

• Develop dbt data models, dashboards, metrics and automation
• Build reporting data models powering external merchant reporting
• Create semantic and metadata layers for AI understanding of Revenue data
• Collaborate with stakeholders to translate requirements into durable data products
• Contribute to version control, code review, and release hygiene
• Develop governance foundations to scale analytics impact

Skills

SQL

dbt

Python

Data modeling

Data visualization

Analytics engineering

AI tool integration

Tools

Sigma

Looker

Tableau

Databricks

Snowflake

Salesforce

Job description

Affirm is seeking an Analytics Engineer II, Full Stack in Revenue Analytics. This remote-from-Poland role focuses on building scalable data products, semantic layers, and governance to support AI-enabled revenue decisions. You’ll own data modeling, metrics, dashboards, and automation end-to-end.

The role requires 3+ years in analytics engineering or BI, with strong SQL, dbt, Python, and data visualization. Collaboration across data, engineering, and business stakeholders is essential.