Staff Data Engineer (Analytics Engineering) at Affirm

, , Poland -

Full Time

Start Date

Immediate

Expiry Date

18 Mar, 26

Salary

442000.0

Posted On

18 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, SQL, Python, Data Transformation Tools, Cloud Data Platforms, Infrastructure-as-Code, Data Modeling, Pipeline Orchestration, Distributed Data Systems, Machine Learning, Data Quality, Observability, Governance, Compliance, Mentorship, Operational Excellence

Industry

Financial Services

Description

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. Join us in building honest financial products that improve lives. At Affirm, we’re reimagining credit to make it more transparent and accessible. We believe in empowering people to buy now and pay later, with no hidden fees or compounding interest. Our Data Platform powers the insights and systems that make this possible. We’re looking for a Staff Data Engineer to design and lead the development of next-generation data infrastructure and pipelines that enable reliable, secure, and scalable access to data across Affirm. This is a highly impactful role where you’ll influence architecture, data strategy, and mentorship across teams. What you’ll do Define and lead the technical strategy and roadmap for Affirm’s data infrastructure and analytics platforms. Architect, build, and scale data pipelines and systems that power analytics, machine learning, and business decision-making. Partner with cross-functional teams (Engineering and Analytics) to deliver data solutions with measurable business impact. Champion data quality, observability, governance, and compliance across Affirm’s global systems. Act as a technical mentor and multiplier, guiding best practices in data modeling, transformation, and code quality. Drive a culture of operational excellence, ensuring data systems are reliable, performant, and well-monitored. Collaborate globally to establish consistent technical patterns and elevate the overall data engineering craft. What We Look For 8+ years of professional experience in Data Engineering or related roles. Advanced skills in SQL, Python, and modern data transformation tools (e.g., DBT, Airflow). Expertise with cloud data platforms (e.g., AWS, GCP, Snowflake, BigQuery) and Infrastructure-as-Code tools (Terraform preferred). Strong background in data modeling, pipeline orchestration, and distributed data systems (e.g., Spark, Kafka). Proven ability to design, deliver, and maintain large-scale, high-quality data systems. Excellent communication and collaboration skills; able to lead through influence. A growth mindset and a passion for mentoring others. Compensation & Benefits Base Pay Grade - O Equity Grade - 4 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). POL base pay range per year: 342,000 zł - 442,000 zł Additional benefits include: Type of employment: Contract of Employment 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 This role is eligible for creative tax benefits, subject to applicable law 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 Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities. We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include: Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process. [For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records. By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.

Responsibilities

The Staff Data Engineer will define and lead the technical strategy for Affirm’s data infrastructure and analytics platforms, architecting and scaling data pipelines that support analytics and business decision-making. This role also involves mentoring and driving a culture of operational excellence across teams.