[All remote jobs](https://jobicy.com/jobs.md)[![Affirm logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/fac7714c-221-1.jpg)](https://jobicy.com/company/affirm.md)[Affirm](https://jobicy.com/company/affirm.md) # Analytics Engineer II, Full Stack (Revenue Analytics) Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/affirm.md)ShareRemote from[Poland](https://jobicy.com/job-region/poland.md)SalaryPLN 226k–346k / yrDepartment[Data Science & Analytics](https://jobicy.com/categories/data-science.md)EmploymentFull TimeExperienceSeniorPublished3 Oct 2026Apply before2 Nov 2026Listing views49Application actions4Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. Affirm is seeking an Analytics Engineer II to build and own revenue data products, reporting infrastructure, semantic foundations, and analytical systems. The role combines analytics engineering, business intelligence, and stakeholder partnership across the Revenue organization. Core work includes developing dbt models, dashboards, metric definitions, automation, and data governance practices. The engineer will also strengthen semantic and metadata layers that support reliable AI use cases and external merchant reporting. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 4/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThe role requires strong hands-on capability across SQL, dbt, Python, cloud warehousing, BI, and semantic data design, along with the ability to convert ambiguous commercial questions into production-quality data products. It also demands frequent communication with technical teams and non-technical revenue stakeholders. ## Salary analysis Estimated compensation compared with the broader PLN market for similar roles. Estimated job medianAbove marketPLN286,000PLN market rangePLN110k–PLN155k0PLN315k AI insightThe disclosed annual base-pay range is PLN 226,000–346,000, with a midpoint of PLN 286,000. For comparison, the estimated US market base-salary range for a mid-level Analytics Engineer focused on revenue analytics is USD 110,000–155,000 annually; this US market benchmark is an estimate and excludes equity and benefits. ## Core skills Skills and capabilities most closely associated with this opportunity. [SQL](https://jobicy.com/jobs?search_keywords=SQL.md)[dbt](https://jobicy.com/jobs?search_keywords=dbt.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[data modeling](https://jobicy.com/jobs?search_keywords=data%20modeling.md)[business intelligence](https://jobicy.com/jobs?search_keywords=business%20intelligence.md)[Snowflake](https://jobicy.com/jobs?search_keywords=Snowflake.md)[Databricks](https://jobicy.com/jobs?search_keywords=Databricks.md)[Tableau](https://jobicy.com/jobs?search_keywords=Tableau.md)[semantic layer](https://jobicy.com/jobs?search_keywords=semantic%20layer.md)[data governance](https://jobicy.com/jobs?search_keywords=data%20governance.md) Sample interview questionsHow would you design a dbt model for a revenue metric used by several reporting teams?I would first align stakeholders on the business definition, grain, source systems, inclusion rules, and ownership of the metric. I would build staged source models, an intermediate transformation layer, and a documented mart model with dbt tests for uniqueness, relationships, accepted values, and freshness where appropriate. I would expose the metric through a governed semantic layer so dashboards use a single consistent definition. Describe how you would approach an ambiguous request to improve revenue reporting. I would begin with discovery sessions to identify the decision being supported, intended users, current pain points, and success measures. I would translate those findings into a small set of deliverables, validate source-data quality and feasibility, and prioritize an incremental solution. Throughout delivery, I would share assumptions and prototypes early so the final data product solves the actual business need. What practices would you use to maintain data quality for external merchant reporting? I would establish source-to-output reconciliations, dbt tests, freshness checks, anomaly monitoring, and clear lineage documentation. For critical metrics, I would define ownership, change-control expectations, and release review procedures. I would also validate report outputs against known merchant samples and investigate variances before deployment. How can semantic layers and metadata improve AI reliability in analytics workflows? Semantic layers provide governed definitions for metrics, dimensions, joins, and calculation logic, reducing ambiguity for both users and AI systems. Metadata such as lineage, owners, documentation, quality status, and examples gives AI tools context to produce more accurate answers. I would pair these foundations with evaluations and human review for high-impact analytical outputs. How do you communicate a complex analytical finding to a non-technical revenue stakeholder? I start with the business question, the key finding, and the recommended action rather than the technical implementation. I use concise visuals, define essential terms, state assumptions and limitations, and quantify expected impact when possible. I make supporting detail available for follow-up while keeping the main message decision-oriented. 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. We’re looking for a curious, driven professional to join our Revenue Analytics team. This builds and owns the data products, reporting infrastructure, semantic foundations, and analytical systems that power Affirm’s Revenue organization. As a Senior Analyst, Revenue Analytics, you’ll build scalable data products that power day-to-day decision-making – owning end-to-end work across data modeling, metric definitions, dashboards, automation, and enablement. You’ll also help strengthen our semantic layer and data governance, laying the foundation for reliable AI. The ideal candidate combines strong technical and analytical skills with the ability to turn ambiguous business questions into durable, well-tested data infrastructure. What you’ll do * Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts * Build and maintain critical reporting data models that power external merchant reporting * Build the semantic, metadata, and context layers that allow AI systems to accurately understand Revenue data, metrics, and business definitions * Partner with Business Systems, engineering, and business stakeholders to translate requirements into durable, well-tested data products * Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows) * Develop processes, governance, and foundations to scale the impact of analytics within Revenue. What we look for * 3+ years of work experience in an analytics engineering or business intelligence role * Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization * Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake) * Understanding of the data foundations required for reliable AI, including semantic layers, metadata, evals, metric definitions, documentation, and data quality * Demonstrated experience integrating AI tools into day-to-day analytics engineering workflows to improve development speed, quality, and scalability * Familiarity with Salesforce and experience supporting commercial areas of the business * Ability to identify user needs and translate them into robust, scalable data products * Ability to start with an ambiguous problem, deconstruct it into tangible steps, and work toward an impactful solution * Ability to communicate findings and recommendations clearly to both technical and non-technical audiences. ### Total rewards We believe the people building honest financial products at Affirm should share in its success. That’s why our total rewards are designed to support your health, growth, financial well-being, and future. In service of our mission, we reward employees through a combination of base pay, equity (from parent company), and comprehensive benefits. Base Pay Grade – K 226 000 zł – 346 000 zł Base pay ranges and placement within those ranges are determined based on several factors, including role, experience, and job-related skills. In addition to base pay, all employees in this role are eligible to receive equity from the parent company each year. This means as Affirm’s parent company grows, employees have the opportunity to share in that growth financially. Equity Grade – 2 (awarded in US Dollars) Affirm Holdings, Inc. Equity Grade example Equity grade: 2 New hire equity: $16,000-$24,000 Annual Refresh: $5,000 Reward equity: $0-$75,000 Affirm also provides flexible spending wallets to all employees for technology and wellbeing related needs, which are reimbursable up to 1390 zł per month. In addition to your compensation, our comprehensive benefits are designed to support you and the people who matter most. Benefits include: * Competitive paid time off, paid public holidays, and additional paid Away Days to rest and recharge. * Comprehensive private healthcare through Lux Med’s Platinum package. * A MultiSport card to support your health and well-being. * Learning and development programs to help you grow professionally. * Family healthcare support through Maven and parental leave support through Parentaly. * Mental well-being support through Lyra, including up to 12 confidential counseling or coaching sessions each year for you and your household members. * Financial well-being support through Northstar, with unlimited access to Certified Financial Advisors and planning tools at no cost to you. * Employee Resource Groups (ERGs) that foster connection and inclusion. * Eligibility for creative tax benefits, subject to applicable law, role, and company policy. Location – Remote Poland The majority of our roles can be located anywhere in Poland. **This job description is not a contractual document, and is not intended to have binding force.** #LI-Remote 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](https://www.affirm.com/global-candidate-privacy-notice) and consent to the use of your personal information as described. 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