Job description
<div class="content-intro"><p>At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.</p></div><p>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.</p> <p>This role focuses on the platform and applications layer of Affirm's data infrastructure — building, operating, and extending systems that enable teams across Affirm to work with data at scale. You will be a core contributor to platform reliability, self-service capabilities, and the roadmap toward agentic data tooling and semantic layer infrastructure.</p> <h2><strong>What You'll Do</strong></h2> <ul> <li><strong>Build and operate core platform capabilities:</strong> Design and implement platform features that enable engineers across Affirm to build, deploy, and operate data applications at scale — covering automated provisioning, deploy pipelines, access control, service lifecycle management, and reliability tooling.</li> <li><str
✍️ Tailored application (cached — grounded in your resume)
72 / 100 honest fit
Daniel is a strong backend fit: he builds and operates Python backend services, AWS-based data processing (Lambda/S3/DynamoDB), and CI/CD automation pipelines — directly relevant to Affirm's platform-and-applications data infrastructure work. His medical-device background instilled the reliability-and-correctness discipline this platform-reliability role demands, and he's a heavy agentic-tooling user, aligning with the team's roadmap toward agentic data tooling. The obvious gap: his experience is in medical-device/telemetry data pipelines rather than large-scale OLTP/OLAP analytics platforms or fintech, so he'd be ramping on data-warehouse-scale systems and semantic-layer infrastructure.
Tailored resume highlights
- Built and operated production Python backend services and validation/data pipelines for connected devices, ensuring reliable, high-throughput data delivery and system performance at scale.
- Implemented AWS-based solutions (Lambda, S3, DynamoDB) supporting scalable data processing and monitoring — the cloud data-infrastructure foundation this platform role builds on.
- Developed Python automation frameworks integrated into Jenkins CI/CD pipelines, enabling reproducible deployments, automated provisioning-style workflows, and faster, more reliable feature delivery.
- Led root-cause analysis of complex, field-found issues across multiple teams — reproducing rare defects in-house and driving cross-team resolution, core to platform reliability and operability.
- Ship production full-stack services end-to-end using LLM/agentic tooling (Claude Code), directly relevant to the team's roadmap toward agentic data tooling and self-service platform capabilities.
"Why this company?" (draft — personalize before sending)
Affirm's Lake Analytics Platform team is building the exact stack I work in — backend data services, AWS-based processing, deploy pipelines, and reliability tooling — but at a scale I want to grow into. Two things pull me. First, the roadmap toward agentic data tooling and semantic layers: I ship production services end-to-end with agentic tooling daily, so that direction is where I already live. Second, reliability as a first-class mission. My background is safety-critical medical-device software, where correctness is a requirement, and I want to bring that discipline to infrastructure teams across Affirm depend on.
Cover letter (review before sending)
Dear Affirm Hiring Team,
I'm applying for the Senior Software Engineer, Backend role on the Lake Analytics Platform team. My work centers on exactly what this role requires: building and operating reliable backend services and data pipelines at scale. At Medtronic, I build Python backend services and AWS-based data processing on Lambda, S3, and DynamoDB, and I develop Python automation frameworks integrated into Jenkins CI/CD to make deployments reproducible and fast — the same provisioning, deploy-pipeline, and reliability tooling your platform mission describes.
Reliability isn't a feature in my background; it's a requirement. In safety-critical medical-device software I led root-cause analysis of complex cross-team issues, reproducing rare defects in-house and driving them to resolution. I bring that operability discipline to platform work.
I'm also a heavy agentic-development user, shipping production services end-to-end with LLM tooling, which maps to your roadmap toward agentic data tooling and self-service capabilities. I'd welcome the chance to help teams across Affirm work with data at scale.
Sincerely,
Daniel Maynard
ATS keywords you have but should add
OLTPOLAPdata platformbatch orchestrationstreaming infrastructureevent-drivenservice lifecycle managementaccess controldeploy pipelinesautomated provisioningplatform reliabilityself-servicedata at scalesemantic layeragentic data tooling
Everything is grounded strictly in your resume — review before you submit. Nothing is auto-sent.