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 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.
What You’ll Do- 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.
- 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.
- 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.
Pay Grade - P
Equity Grade - 7
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).
CAN base pay range per year: 181,000 - 241,000
This posting is for an existing vacancy.
#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.
Skills Required
- 8+ years of experience in software engineering, data infrastructure, or data platform engineering
- 2+ years of technical leadership or hands-on leadership building critical data infrastructure
- Hands-on experience with Apache Iceberg
- Hands-on experience with Spark
- Hands-on experience with Snowflake (RBAC, dynamic data masking, warehouse tuning, query profiling, cost management)
- Experience with cloud-native data lake/storage architectures
- Experience with data governance: RBAC/ABAC, lineage, classification, privacy controls, and policy enforcement
- Experience with analytics engineering tools and practices (dbt or equivalent, data modeling, testing, CI/CD)
- Proficiency in Python, SQL, or JVM-based languages (Java/Scala)
- Familiarity with Infrastructure as Code tools (Terraform or similar) for managing data infrastructure
- Bachelor's degree in a related field or equivalent practical experience
What the Team is Saying
Affirm Compensation & Benefits Highlights
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Healthcare Strength — Benefits include comprehensive medical, dental, vision, and robust mental‑health programs, with $0 employee medical premiums for certain plans. Feedback suggests this combination makes coverage both strong and cost‑effective.
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Parental & Family Support — Birth and non‑birth parents receive 18 weeks of fully paid leave plus a four‑week, full‑pay return‑to‑work transition, alongside family‑planning support. Feedback suggests these policies are a standout strength for those planning or growing families.
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Leave & Time Off Breadth — Generous/flexible PTO is augmented by 20 company‑wide Away Days and additional options like “Life Happens Leave.” Feedback suggests the mix enables both collective recharge and personal time away.
Affirm Insights
What We Do
At Affirm, we help people say yes to the things that matter with flexible, transparent ways to pay over time. No hidden fees, no compound interest, and no fine print—just a smarter way to spend.
Why Work With Us
Who is an Affirmer? /noun/ Someone who believes finance shouldn’t be complicated. We come from a diverse set of backgrounds and we’re driven by the desire to improve lives through honest financial products. We define success by challenging one another to bring our best ideas to every single project—and we have fun while doing it.
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Affirm Offices
Remote Workspace
Employees work remotely.
Affirm is a remote-first company! Our employees can work anywhere in the U.S. but if an office is more your style, we have office locations in San Francisco, Chicago, New York City, and Pittsburgh.
