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.
The Streaming team at Affirm forms the backbone of several online and offline workloads at Afirm and drives the strategy for event driven architecture, stream processing, replication, data exploration, discovery and validation. We leverage existing open source technologies like Kafka, Flink, Spark and also build our own as needed to design and build real-time data processing pipelines that handle massive volumes of data across our distributed systems.
As a member of our team you would spend time identifying and executing on new use cases of streaming data infrastructure and frameworks , designing and scaling our existing infrastructure and working closely with other teams to promote the optimal use of data at the company. This role requires deep expertise in stream processing technologies and a passion for building scalable, fault-tolerant data infrastructure.
What You'll Do
- You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery.
- You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs.
- You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them.
- You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts.
- You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks.
- You will help develop talent on your team by providing feedback and guidance, and leading by example.
What We Look For
- 5+ years of industry experience in building large scale production systems.
- Strong hands on experience with Apache Kafka for large-scale event streaming and message queueing
- Experience building and operating robust and highly available infrastructure.
- Experience working with Apache Iceberg and data platforms like Snowflake, Glue or Databricks
- Expertise with at least one stream processing frameworks like Spark, Samza, Flink, Beam etc.
- Solid programming skills in Python, Java or Kotlin.
- Experience with Apache Iceberg table format, CDC (Change Data Capture) tools is a strong plus
- Knowledge of Relational and NoSQL databases is a plus.
- Experience leading technical projects and mentoring junior engineers
- You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others.
- You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely.
- Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
- You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
- This position requires either equivalent practical experience or a Bachelor’s degree in a related field.
Base Pay Grade- N
Equity Grade- 8
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 equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
USA base pay range (CA, WA, NY, NJ, CT) per year: $190,000 - $240,000
USA base pay range (all other U.S. states) per year: $169,000 - $219,000
#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.
[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.
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