Staff Backend Software Engineer, Affirm
Streaming
$200-275k
Actual salary range is dependent on location. Offers ESPP
POS installment loans
Be an early applicant
POS installment loans
1001+ employees
Be an early applicant
$200-275k
Actual salary range is dependent on location. Offers ESPP
1001+ employees
Company mission
To deliver honest and transparent financial products that improve users' lives.
Role
Who you are
- This role requires deep expertise in stream processing technologies and a passion for building scalable, fault-tolerant data infrastructure
- 8+ 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
What the job involves
- 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
- Design and build data infrastructure systems, services and tools to handle new Affirm products and business requirements that securely scale over millions of users and their transactions
- Build and optimize high-throughput, low-latency data pipelines for critical business applications
- Build frameworks and services which will be used by other engineering teams at Affirm to manage billions of dollars in loans and power customer experiences
- Help support the Streaming team that forms the backbone for several online and offline workloads at affirm
- Improve the reliability and efficiency of the Data Platform at scale and high availability
- Collaborate with other teams at Affirm, including ML and Analytics, to deliver streaming solutions based on various use-cases and best practices
- Monitor, troubleshoot, and maintain production streaming systems, ensuring high availability and reliability of data systems
Our take
Affirm offers point-of-sale loans to consumers, working with merchants like Shopify, KAYAK, and Walmart. Buy now, pay later transactions have grown in popularity in recent years, and this business is tapping into the market with a totally different approach to credit - by delivering the Affirm card, the first US debit card with the option to pay-over-time.
Boasting over 21M consumers and 337,000+ merchants, the company offers flexible payback options, ranging from 3 to 36 months. The interest rates run between 0% and 30%, so, while they are not necessarily the cheapest option, Affirm prides itself on having no fees for late payments, no hidden charges, and total transparency about what people will pay before they take out a loan.
Affirm collects payments from the customers and pays the merchants directly, shouldering the risk itself. The company has boosted its market share, expanding its availability beyond the US to include most of Canada, and continues to launch new features and create new partnerships towards bettering its offering.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
-11% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Sep 2020
$500m
SERIES G
Apr 2019
$300m
SERIES F
Total funding: $1.1bn
Company benefits
- Compensation: We have a simple, flexible, and transparent remote-first compensation structure so you can make the best decisions for yourself and your family
- Spending Wallets: Access tech, food, lifestyle, and family planning wallets for your expenses
- Supportive Communities: Get involved with our employee resource groups and community groups
- Remote-first Workforce: If your role is remote, you can set up shop anywhere in your home country
- Generous Time Off: Take the time you need when life happens
- Health Benefits: Get a plan that fits your needs
- Mental Healthcare: Take care of your mind with great mental health programs
- Parental Leave: Birth and non-birth parents get 18 weeks’ paid leave. Plus, a 4-week return-to-work transition program, at full base pay
- Away Days: We offer 20 company-wide paid days off—which help our teams collectively pause to recharge
- Learning & Development: Engage in exciting learning programs to level up your growth
Company HQ
Chinatown, San Francisco, CA
Leadership
Max Levchin
(Co-Founder & CEO)Has founded/co-founded numerous companies, holding various executive positions at each, including Paypal, Slide, Glow, HVF Labs, and SciFi VC. Also worked at large brands including Google, Yelp, Yahoo, and Evernote.
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