data
Posted 1 weeks agoStaff Software Engineer, Backend (Lake Analytics Platform)
at Affirm
CanadaRemote
Responsibilities
- 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.
- 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.
- 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.
- Build teams: Mentor engineers, raise technical quality, and foster an inclusive culture of design rigor, operational excellence, and continuous learning. What We Look For
Requirements
- 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.
- 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
- 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.
- 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 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.
- experience with Apache Iceberg, Spark, and cloud-native data lake architectures.
- 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.
- experience or a Bachelor’s degree in a related field. Pay Grade - P Equity Grade - 7
- Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office.
Experience
- Experience: 8+ years of
Benefits
- 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,
- 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
- 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
Additional details
- 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.
- Our mission is to provide trustworthy, intuitive, and cost-efficient solutions for Affirmers to secure, store, analyze, and transform data at exceptional scale.
- 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.
- Education: This position requires equivalent practical
- 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.
- A limited number of roles remain office-based due to the nature of their job responsibilities.