Analytics Engineer II

About the Role

The role requires a deep understanding of data systems, pipelines, and workflows. You will be expected to identify, troubleshoot, and resolve production data issues, and drive root-cause fixes. Your expertise in SQL, dbt, and cloud data warehouses will be essential in optimizing performance and cost. You will also partner with engineering and business stakeholders to translate requirements into durable, well-tested data assets.

The Financial Systems team at Affirm is responsible for owning the data and reporting foundation for Accounting. The team is building a single source of truth for financial information using dbt and Snowflake to enable scalable BI and process automation across the organization. As an Analytics Engineer, you will play a key role in this effort, working closely with the team to ensure the success of the project.

What You Will Do

• Build and maintain dbt models and core datasets that support Accounting reporting and downstream automation use cases
• Improve platform reliability through strong testing patterns, alerting, and runbooks
• Own and document data pipelines and lineage, ensuring changes are understandable and auditable
• Identify, troubleshoot, and resolve production data issues, and drive root-cause fixes
• Optimize performance and cost in Snowflake and dbt to support scaling needs
• Partner with engineering and business stakeholders to translate requirements into durable, well-tested data assets
• Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows)
• Collaborate with the Financial Systems team to ensure the operational reliability of the pipelines that power reporting, reconciliations, and automation
• Develop and maintain strong relationships with stakeholders to ensure data needs are met
• Stay up-to-date with industry trends and emerging technologies in data engineering and analytics

What We Are Looking For

• 3+ years of experience in analytics engineering, data engineering, or similar roles working with production data systems
• Strong SQL skills and hands-on experience building in dbt (modeling, testing, documentation)
• Experience operating in a modern development workflow: Git and pull-request based collaboration (GitHub preferred)
• Familiarity with standard IDEs and collaborative debugging practices
• Experience working with cloud data warehouses (Snowflake preferred)
• A strong sense of ownership and comfort working in ambiguous, fast-moving environments
• Excellent communication and collaboration skills
• Ability to work independently and as part of a team
• Strong problem-solving skills and attention to detail

Nice to Have

• Finance/accounting data familiarity (e.g., close concepts, reconciliations, ledger-style modeling)
• Experience with integration/automation platforms (Workato, Fivetran, or similar)
• Experience supporting reporting layers and BI tooling
• Working knowledge of Python for data manipulation and automation
• Familiarity with CI pipelines and quality gates for code quality, testing, and build validation

Benefits and Perks

• Competitive base pay (POL base pay range per year: 226,000 zł - 346,000 zł)
• Equity rewards offered by Affirm Holdings, Inc. (parent company)
• 100% subsidized medical coverage, dental and vision for you and your dependents
• Flexible Spending Wallets for health, wellness, and tech spending
• Opportunity to work with a talented team of professionals in a fast-growing company
• Professional development opportunities and support for ongoing education and training
• Access to cutting-edge technologies and tools
• Remote work options and flexible working hours
• Comprehensive benefits package, including paid time off and holidays,

• Tip: Make sure to highlight your experience with dbt, Snowflake, and cloud data warehouses in your application, as these are key skills for the role.
• To stand out, showcase your ability to work independently and as part of a team, and demonstrate your problem-solving skills and attention to detail.
• When preparing for the interview, review the company's technology stack and be ready to discuss your experience with similar tools and technologies.
• Be prepared to provide examples of your experience with data pipelines, workflows, and automation, and explain how you have optimized performance and cost in previous roles.
• Consider creating a portfolio of your work, including examples of your dbt models, data visualizations, and other relevant projects, to demonstrate your skills and experience to the hiring team.
• Don't be afraid to ask questions during the interview, such as what a typical day looks like in the role, or what opportunities there are for professional development and growth within the company.