Affirm Visa Sponsorship Jobs USA
Affirm is a leading U.S. fintech company known for its buy now, pay later platform. It has a strong track record of sponsoring work visas across engineering, data, and product roles, making it a well-regarded option for international candidates targeting the Banking & Financial Services sector.
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Get Access To All JobsINTRODUCTION
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. Affirm's engineering team is building a large-scale, highly available, and global infrastructure that is shared across multiple financial products. Ensuring that our infrastructure is accessible to all engineers is critical to the success of the business. We pride ourselves on our culture across engineering of engaging in thorough technical design review, operational excellence, and capable incident response and analysis.
The Data and Storage Services team is responsible for Affirm's data infrastructure across OLTP and OLAP systems, spanning critical online checkout databases, batch orchestration, streaming infrastructure, event-driven frameworks, BI, analytics tooling, large-scale data platforms, and agentic data tools such as semantic layers and internal platform data applications. Our mission is to provide trustworthy, intuitive, and cost-efficient solutions for Affirmers to secure, store, analyze, and transform data at exceptional scale.
This role will focus on Affirm's Lakehouse Platform, including Apache Iceberg as a foundational technology for scalable analytical data storage, table management, schema evolution, and interoperability across compute engines such as Spark and Snowflake.
- Influence technical strategy: Define and drive the long-term technical roadmap for Affirm's Lakehouse Platform across Apache Iceberg, Spark, Snowflake, and cloud-native storage, balancing scalability, reliability, governance, performance, and cost.
- Design and develop: Architect and implement platform capabilities that make analytical data secure, trustworthy, discoverable, and easy to use across Affirm's engineering, analytics, machine learning, and business teams.
- Strengthen governance and access controls: Design and operate secure, auditable data access capabilities across Snowflake and the lakehouse platform, including RBAC, dynamic data masking, cataloging, lineage, classification, and privacy policy enforcement.
- Improve analytics engineering foundations: Partner with Analytics Engineering to evolve data modeling, transformation pipelines, testing frameworks, documentation standards, and data quality practices that enable trustworthy self-service analytics.
- Operate at scale: Establish best practices for lakehouse operations, including schema evolution, table maintenance, partitioning, compaction, observability, incident response, production support, and readiness for on-call operations.
- Optimize performance and cost: Identify and execute improvements across analytical compute and storage, including Snowflake warehouse tuning, query optimization, storage layout, lifecycle management, cost attribution, and operational efficiency.
- Collaborate cross-functionally: Partner with Infrastructure, Lakehouse Analytics, Analytics Engineering, Machine Learning, BI, Product Engineering, and SRE to translate stakeholder needs into durable platform architecture.
- Innovate: Stay ahead of industry trends in lakehouse architecture, open table formats, analytical compute engines, data governance, privacy engineering, semantic layers, agentic data tools, and AI-ready data infrastructure.
- Build teams: Mentor engineers, raise technical quality, and foster an inclusive culture of design rigor, operational excellence, and continuous learning.
What We Look For
- Lakehouse Platform Expertise: Proven experience architecting, building, launching, and operating large-scale OLAP systems, lakehouse platforms, or analytical data infrastructure using technologies such as Apache Iceberg, Spark, Snowflake, and cloud-native storage.
- Snowflake Platform Expertise: Hands-on experience with Snowflake or comparable analytical data warehouses, including RBAC, dynamic data masking, warehouse optimization, query profiling, clustering, and cost management.
- Data Platform Architecture: Strong understanding of table formats, schema evolution, partitioning, compaction, query performance, data lifecycle management, observability, and cost optimization for analytical systems.
- Governance and Trust: Experience designing secure, reliable, and governed data platforms, including RBAC/ABAC, data quality, lineage, classification, privacy controls, policy enforcement, and operational compliance.
- Analytics Engineering Foundations: Experience with dbt or similar transformation frameworks, data modeling best practices, testing, documentation, CI/CD, and data quality practices for analytical pipelines.
- Agentic Data Tools: Experience building or shaping semantic layers, self-service analytics platforms, internal data applications, or AI-enabled data tools that improve data accessibility and usability.
- Technical Leadership: Demonstrated ability to set technical direction, lead ambiguous platform initiatives, mentor engineers, and influence roadmaps across teams while staying close to implementation details.
- Collaboration: Strong ability to partner with engineering, analytics, machine learning, BI, product, and infrastructure teams to translate business needs into durable technical solutions.
- Communication Skills: Excellent communication skills, with the ability to clearly articulate technical concepts, tradeoffs, and recommendations to technical and non-technical stakeholders.
Qualifications
- Experience: 8+ years of experience in software engineering, data infrastructure, or data platform engineering, with 2+ years of technical leadership responsibilities.
- Hands-on Leadership: Hands-on experience leading teams to build critical data infrastructure.
- Snowflake / Analytical Warehouses: Hands-on experience with Snowflake or comparable analytical data warehouses, including access control, data masking, query optimization, and cost management.
- Lakehouse and Big Data: Strong experience with Apache Iceberg, Spark, and cloud-native data lake architectures.
- Analytics Engineering: Experience with dbt or equivalent transformation frameworks, including data modeling, testing, documentation, and CI/CD practices.
- Programming Skills: Proficiency in Python, SQL, or JVM-based languages, with a strong emphasis on clean, maintainable, production-quality systems.
- Infrastructure as Code: Familiarity with Terraform or similar automation tools for managing data infrastructure.
- Education: This position requires equivalent practical experience or a Bachelor's degree in a related field.
Base Pay Grade - P
Equity Grade - 13
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.
USA base pay range (CA, WA, NY, NJ, CT) per year: $230,000 - $290,000
USA base pay range (all other U.S. states) per year: $204,000 - $264,000
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.
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.
INTRODUCTION
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. Affirm's engineering team is building a large-scale, highly available, and global infrastructure that is shared across multiple financial products. Ensuring that our infrastructure is accessible to all engineers is critical to the success of the business. We pride ourselves on our culture across engineering of engaging in thorough technical design review, operational excellence, and capable incident response and analysis.
The Data and Storage Services team is responsible for Affirm's data infrastructure across OLTP and OLAP systems, spanning critical online checkout databases, batch orchestration, streaming infrastructure, event-driven frameworks, BI, analytics tooling, large-scale data platforms, and agentic data tools such as semantic layers and internal platform data applications. Our mission is to provide trustworthy, intuitive, and cost-efficient solutions for Affirmers to secure, store, analyze, and transform data at exceptional scale.
This role will focus on Affirm's Lakehouse Platform, including Apache Iceberg as a foundational technology for scalable analytical data storage, table management, schema evolution, and interoperability across compute engines such as Spark and Snowflake.
- Influence technical strategy: Define and drive the long-term technical roadmap for Affirm's Lakehouse Platform across Apache Iceberg, Spark, Snowflake, and cloud-native storage, balancing scalability, reliability, governance, performance, and cost.
- Design and develop: Architect and implement platform capabilities that make analytical data secure, trustworthy, discoverable, and easy to use across Affirm's engineering, analytics, machine learning, and business teams.
- Strengthen governance and access controls: Design and operate secure, auditable data access capabilities across Snowflake and the lakehouse platform, including RBAC, dynamic data masking, cataloging, lineage, classification, and privacy policy enforcement.
- Improve analytics engineering foundations: Partner with Analytics Engineering to evolve data modeling, transformation pipelines, testing frameworks, documentation standards, and data quality practices that enable trustworthy self-service analytics.
- Operate at scale: Establish best practices for lakehouse operations, including schema evolution, table maintenance, partitioning, compaction, observability, incident response, production support, and readiness for on-call operations.
- Optimize performance and cost: Identify and execute improvements across analytical compute and storage, including Snowflake warehouse tuning, query optimization, storage layout, lifecycle management, cost attribution, and operational efficiency.
- Collaborate cross-functionally: Partner with Infrastructure, Lakehouse Analytics, Analytics Engineering, Machine Learning, BI, Product Engineering, and SRE to translate stakeholder needs into durable platform architecture.
- Innovate: Stay ahead of industry trends in lakehouse architecture, open table formats, analytical compute engines, data governance, privacy engineering, semantic layers, agentic data tools, and AI-ready data infrastructure.
- Build teams: Mentor engineers, raise technical quality, and foster an inclusive culture of design rigor, operational excellence, and continuous learning.
What We Look For
- Lakehouse Platform Expertise: Proven experience architecting, building, launching, and operating large-scale OLAP systems, lakehouse platforms, or analytical data infrastructure using technologies such as Apache Iceberg, Spark, Snowflake, and cloud-native storage.
- Snowflake Platform Expertise: Hands-on experience with Snowflake or comparable analytical data warehouses, including RBAC, dynamic data masking, warehouse optimization, query profiling, clustering, and cost management.
- Data Platform Architecture: Strong understanding of table formats, schema evolution, partitioning, compaction, query performance, data lifecycle management, observability, and cost optimization for analytical systems.
- Governance and Trust: Experience designing secure, reliable, and governed data platforms, including RBAC/ABAC, data quality, lineage, classification, privacy controls, policy enforcement, and operational compliance.
- Analytics Engineering Foundations: Experience with dbt or similar transformation frameworks, data modeling best practices, testing, documentation, CI/CD, and data quality practices for analytical pipelines.
- Agentic Data Tools: Experience building or shaping semantic layers, self-service analytics platforms, internal data applications, or AI-enabled data tools that improve data accessibility and usability.
- Technical Leadership: Demonstrated ability to set technical direction, lead ambiguous platform initiatives, mentor engineers, and influence roadmaps across teams while staying close to implementation details.
- Collaboration: Strong ability to partner with engineering, analytics, machine learning, BI, product, and infrastructure teams to translate business needs into durable technical solutions.
- Communication Skills: Excellent communication skills, with the ability to clearly articulate technical concepts, tradeoffs, and recommendations to technical and non-technical stakeholders.
Qualifications
- Experience: 8+ years of experience in software engineering, data infrastructure, or data platform engineering, with 2+ years of technical leadership responsibilities.
- Hands-on Leadership: Hands-on experience leading teams to build critical data infrastructure.
- Snowflake / Analytical Warehouses: Hands-on experience with Snowflake or comparable analytical data warehouses, including access control, data masking, query optimization, and cost management.
- Lakehouse and Big Data: Strong experience with Apache Iceberg, Spark, and cloud-native data lake architectures.
- Analytics Engineering: Experience with dbt or equivalent transformation frameworks, including data modeling, testing, documentation, and CI/CD practices.
- Programming Skills: Proficiency in Python, SQL, or JVM-based languages, with a strong emphasis on clean, maintainable, production-quality systems.
- Infrastructure as Code: Familiarity with Terraform or similar automation tools for managing data infrastructure.
- Education: This position requires equivalent practical experience or a Bachelor's degree in a related field.
Base Pay Grade - P
Equity Grade - 13
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.
USA base pay range (CA, WA, NY, NJ, CT) per year: $230,000 - $290,000
USA base pay range (all other U.S. states) per year: $204,000 - $264,000
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.
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.
Job Roles at Affirm
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Get Access To All JobsTips for Finding Affirm Visa Sponsorship Jobs USA
Target engineering and data roles first
Affirm's strongest sponsorship history sits in software engineering, machine learning, and data science. These teams have the most consistent hiring of international talent, so focus your search on technical roles aligned with Affirm's core fintech infrastructure.
Understand Affirm's fintech compliance environment
Banking and financial services employers face stricter regulatory hiring requirements. Demonstrating familiarity with fintech compliance, risk frameworks, or consumer credit regulations signals you can contribute immediately, which strengthens your case for sponsorship consideration.
Apply early in the calendar year for H-1B timing
Affirm sponsors H-1B visas, and H-1B cap registrations open in March. Securing an offer before February gives Affirm enough lead time to file your registration and prepare petition documents without a rushed process.
Highlight OPT or CPT experience in your application
Affirm sponsors F-1 OPT and CPT, making it a viable path for students transitioning to full-time roles. If you have prior internship or STEM OPT experience in fintech or payments, lead with it, it reduces employer sponsorship risk and friction.
Use verified sponsorship data to prioritize your outreach
Not every Affirm role will be open to sponsorship. Migrate Mate surfaces verified sponsors so you can filter by real sponsorship history and focus your applications on positions where international candidates have actually been hired.
Prepare for a structured, multi-stage interview process
Affirm typically runs technical screens, system design rounds, and behavioral interviews. For sponsored roles in financial technology, expect questions around scaling payments systems, fraud detection, or credit risk, prepare domain-specific examples alongside standard software engineering preparation.
Frequently Asked Questions
Does Affirm sponsor H-1B visas?
Yes, Affirm sponsors H-1B visas. The company has an active sponsorship track record with H-1B petitions concentrated in technical and product roles. If you're targeting Affirm on H-1B, aim to have an offer in place before the cap registration window opens in early March, since petitions require preparation time before USCIS filing deadlines.
Which visa types does Affirm sponsor?
Affirm sponsors H-1B, TN visa, F-1 OPT, and F-1 CPT visas, as well as permanent residence pathways including EB-2 and EB-3 Green Cards. This range makes Affirm a viable employer across multiple stages of an international candidate's career, from student internships through to long-term work authorization and permanent residency.
Which departments or roles at Affirm are most likely to be sponsored?
Sponsorship at Affirm is most concentrated in software engineering, machine learning, data science, and product management. These functions sit at the core of Affirm's fintech platform and have the most consistent demand for specialized talent. Finance, risk, and compliance roles in the Banking & Financial Services space also see sponsorship activity, though at lower volumes than engineering.
How do I find open sponsored roles at Affirm?
Migrate Mate is the most efficient way to find Affirm roles open to visa sponsorship. It aggregates positions from verified sponsoring employers, letting you filter by visa type and company so you're only applying where international candidates have a real shot. From there, apply directly through Affirm's careers page and flag your sponsorship needs early in the recruiter conversation.
How do I approach Affirm's hiring process as a visa sponsorship candidate?
Be upfront about your visa status in your initial recruiter screen. Affirm has an established sponsorship process, so recruiters are familiar with H-1B and OPT timelines. Prepare for a multi-stage technical process and, if you're on OPT, make sure your STEM OPT extension or cap-gap situation is clearly explained so the recruiting team can align hiring timelines with your authorization window.