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Analyst II, Full Stack

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Remote from
Spain
Salary
EUR 63k–99k / yr
Employment
Full Time
Experience
Open level
Published
Apply before
2 Nov 2026
Listing views
19
Application actions
0
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AI Summary

The role, at a glance.

Affirm is hiring an Analytics Engineer to operate and improve the financial data platform that supports accounting reporting, reconciliations, and automation. The role centers on building dbt models, maintaining core datasets, improving pipeline reliability, and resolving production data issues in Snowflake. It requires strong SQL, dbt, Git-based development practices, documentation, testing, and stakeholder partnership. The position is remote within Spain and includes operational ownership of scalable, auditable financial data assets.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThis is a mid-level production data-platform role requiring hands-on dbt and Snowflake expertise alongside ownership of reliability, performance, testing, and incident resolution. Finance-facing datasets add a need for accuracy, auditability, and clear cross-functional communication.

Salary analysis

Estimated compensation compared with the broader EU market for similar roles.

Estimated job medianBelow market
€81,000
EU market range€110k–€150k
AI insightThe disclosed base-pay range is €63,000–€99,000 per year, with a midpoint of €81,000 per year. The estimated US market range for a mid-level Analytics Engineer with dbt, Snowflake, and production data-platform responsibilities is approximately $110,000–$150,000 annually; this market comparison is an estimate and is not a conversion of the Spain-based offer.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a dbt model for an accounting reconciliation dataset?

I would first define the source systems, grain, reconciliation rules, and expected control totals with accounting stakeholders. I would build layered staging, intermediate, and mart models, add unique/not-null/relationship tests, document lineage, and create exception outputs that make discrepancies actionable.

Describe how you would investigate a production data-quality incident.

I would assess the impact and scope, validate the failing model and upstream sources, and use job logs, freshness checks, and recent code changes to isolate the cause. I would communicate status early, implement a safe fix or rollback, validate downstream results, and document the root cause and preventive controls in a runbook.

What techniques would you use to improve Snowflake and dbt performance and cost?

I would inspect query profiles and warehouse usage, reduce unnecessary scans, optimize joins and incremental models, and materialize models appropriately. I would also schedule workloads thoughtfully, monitor expensive jobs, and validate that performance changes preserve correctness and test coverage.

How do you maintain reliable collaboration in a GitHub-based analytics engineering workflow?

I use focused pull requests, meaningful commit messages, peer review, automated tests, and CI checks before deployment. I also maintain model documentation and release notes so reviewers and downstream users understand schema, logic, lineage, and potential impact.

How would you translate an ambiguous stakeholder request into a durable data asset?

I would clarify the business decision, metric definitions, data grain, freshness expectation, consumers, and acceptance criteria. Then I would propose a documented model contract, build and test the asset iteratively, validate outputs with stakeholders, and establish ownership and monitoring after release.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.

Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building a single source of truth for financial information using dbt and Snowflake to enable scalable BI and process automation across the org.

We are hiring an Analytics Engineer focused on maintaining and optimizing our finance data platform, improving reliability, efficiency, and performance of our pipelines and core datasets. This role is ideal for someone who enjoys operational ownership, building strong foundations, and making data systems easier and safer to run at scale.

What You’ll 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).

What We Look 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.

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.
  • Interest in applying AI-assisted development responsibly within engineering guardrails.

Compensation & Benefits

Base Pay Grade – K

Equity Grade – 3

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).

ESP base pay range per year: €63,000 – €99,000

Additional benefits include:

  • Flexible Spending Wallets for tech, food and lifestyle
  • Away Days – wellness days to take off work and recharge
  • Learning & Development programs
  • Parental benefits
  • Employee Resource & Community Groups

We are able to offer visa sponsorship for this role, but do require that someone is based in Spain for the role.

Location – Remote Spain

Remote-first with flexibility built in
Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

Benefits designed for you
Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:

  • Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
  • Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
  • Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
  • Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.

We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.

For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.

By clicking “Submit Application,” you acknowledge that you have read Affirm’s Global Candidate Privacy Notice and consent to the use of your personal information as described.

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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