Prosper - Staff Software Engineer (Data Platforms)
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Requirements
• BS in EE/CS with 12+ years of experience or MS in EE/CS with 8+ years of experience. • Deep expertise in object-oriented Python within an enterprise environment. Experience in Java, C#, or Go is a major plus. • Software-First Mindset: You treat data infrastructure as a software product, not a series of one-off scripts or data pipelines. • Production DevOps: Proficiency with Docker, Kubernetes, CI/CD, and Infrastructure as Code (Terraform) within modern cloud providers. • Data Fluency: Strong SQL (e.g. BigQuery, PostgreSQL) and an understanding of how to build systems around data warehouses. • Modern Workflow: Proficient with LLM-assisted development (e.g. Cursor) to accelerate delivery while ensuring you can understand, explain and defend every line. • Ownership: A track record of taking complex engineering problems from an “idea” or “concept” to "stable service." • Take-Home Assignment: Analyze a real-world problem, propose solutions, and present findings, evaluating analytical, strategic thinking, and presentation skills. • Technical Interview: Deeper dive into coding skills. • Team Interview: Meet team members for collaborative discussions, problem-solving, or technical exercises. • $167,000 - $245,000 a year • Compensation details: The salary for this position is $167k - $245k annually, plus bonus and generous benefits. In determining your salary, we will consider your location, experience, and other job-related factors. • Accountability at all levels drives results • www.prosper.com • Our Story & Team // Our Blog • Applicants have rights under Federal Employment Laws. • Family & Medical Leave Act (FMLA) • Equal Employment Opportunity (EEO) • Employee Polygraph Protection Act (EPPA) • California applicants: please click here to view our California Consumer Privacy Act (“CCPA”) Notice for Applicants, which describes your rights under the CCPA. • At Prosper, we're looking for people with passion, integrity, and a hunger to learn. We encourage you to apply even if your experience doesn't precisely match the job description. Your unique skill set and diverse perspective will stand out and set you apart from other candidates. Prosper thrives with people who think outside of the box and aren't afraid to challenge the status quo. We invite you to join us on our mission to advance financial well-being. • Prosper is committed to an inclusive and diverse workplace. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law, including the San Francisco Fair Chance Ordinance. Prosper will consider for employment qualified applicants who are non-US citizens and will provide green card sponsorship. • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Responsibilities
• We need an Enterprise Python Expert to join our Data Engineering team. While you’ll work within our data ecosystem, your primary focus is high-quality Software Engineering: designing and building pipelines and services, improving system architecture, and writing clean, scalable code with our Google cloud eco-system (GCP). • How you’ll make an impact • Architect Services: Design and stand up backend services and APIs that power our data platform. • Build for Scale: Transition us from simple scripts to production-grade software with logging, alerting, and automated testing. • Modernize Tooling: Evaluate and implement new frameworks that improve system reliability and developer velocity. • Collaborate: Partner with analysts, software engineers and infrastructure teams to ensure our data services are fast, secure, and easy to consume. • Lead by Example: Set the standard for Python excellence, performing deep code reviews and mentoring the team on SDLC best practices.
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