Software Engineer, Product Security Data Platforms
Senior Software Engineer building scalable security data pipelines and streaming APIs at Stripe. Lead design of high-throughput event processing, security signal logic, and developer-friendly platforms; requires distributed systems and data engineering expertise.
About the job
Responsibilities
- Architect scalable foundations: Design and implement a highly available, low-latency pipeline capable of processing and augmenting millions of events per second into structured security telemetry.
- Build API-first products: Develop the core services and streaming APIs that enable enterprise customers to seamlessly ingest security signals into their own internal security operations centers and analytics tools.
- Engineer security signals: Partner with security researchers and threat detection experts to build the logic that identifies anomalous behavior and surfaces high-fidelity security insights.
- Define technical strategy: Lead the technical roadmap for the platform, making critical decisions on data modeling, storage strategies, and the abstraction layers that will support future security products.
- Drive engineering excellence: Set the bar for code quality, system resilience, and operational maturity for a product that requires 99.99%+ availability.
- Collaborate cross-functionally: Work closely with the Stripe core platform and data teams to leverage global infrastructure while ensuring security data remains isolated and protected.
Minimum Requirements
- 2+ years of professional software development experience, with a history of shipping and maintaining complex, large-scale systems.
- Expertise in data engineering and distributed systems, with deep experience building and operating high-throughput data pipelines (e.g., Kafka, Flink, Spark, or similar streaming technologies).
- Strong programming fundamentals, significant experience in languages like Java, C++, or Rust.
- Operational mindset, experience maintaining business-critical services with high availability requirements, on-call rotation, and a strong focus on observability and debugging.
- Communication and collaboration skills, excellent technical writing skills for drafting design documents and the ability to mentor other engineers while collaborating with non-technical stakeholders.
Preferred Qualifications
- Security domain knowledge, with prior experience building security analytics, threat detection systems, or observability platforms.
- Platform engineering with experience building "as-a-service" infrastructure where the primary users are other engineers or external developers.
- Cloud native infrastructure, with prior experience with AWS, Kubernetes, and infrastructure-as-code (Terraform).
- Product intuition and a desire to work on "0-to-1" initiatives where you help define the product requirements and user experience alongside engineering.
- Front-end or full stack experience is a plus, particularly with React or TypeScript.
Skills
Java, C++, Rust, Kafka, Flink, Spark, AWS, Kubernetes, Terraform, React, TypeScript
Similar jobs
Data Engineering jobs
Bevi
Boston, MA
Build and maintain dbt models, Snowflake semantic layers, and ingestion pipelines across business functions while improving data quality and resilience. The role requires 4–6 years of analytics or data engineering experience, strong dbt and SQL expertise, and a quantitative bachelor's degree.
Anthropic
San Francisco, CABuild and govern quote-to-cash data models and products integrating Salesforce, CPQ, billing, and finance systems. The role requires 5+ years of data engineering experience, strong SQL and Python skills, and expertise in self-service analytics for GTM teams.
Cloudflare
Atlanta, GABuild and scale distributed data platforms, database systems, delivery services, and APIs, with emphasis on reliability, performance, observability, and data integrity. Requires 3+ years of software development experience with distributed systems and databases; Golang experience is preferred.
Astera
Emeryville, CA
Oversee the lifecycle, quality, governance, and publication of research data across scientific programs. The role requires 3–5+ years of research data-management experience, strong metadata and FAIR-data expertise, and the ability to collaborate with researchers and engineers.
Upside
Washington, DCOwn and evolve trusted data models for Marketing and Product use cases, from design and testing through monitoring and documentation. The role requires 3–5 years of data or analytics engineering experience, strong SQL and Python, dbt expertise, and Snowflake or comparable warehouse experience.