> Markdown version of [/jobs/ext/4617089-software-engineer-data-foundations](https://www.wearedevelopers.com/jobs/ext/4617089-software-engineer-data-foundations). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, Data Foundations - **Company:** Whatnot Inc. - **Location:** Los Angeles, CA, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Amazon S3, Data Analysis, Audit Trail, BigQuery, Cloud Computing, Content Analysis, Continuous Integration, Data Governance, Data Infrastructure, Data Systems, DevOps, Distributed Systems, Github, Python (Programming Language), Machine Learning, Uptime, Site Reliability Engineering Practices, Data Streaming, Data Processing, Google Cloud, Real Time Systems, Snowflake, Data Lakes, Solid Principles, Kubernetes, Infrastructure Automation Frameworks, Apache Flink, Apache Kafka, Operational Systems, Api Design, Terraform, Stream Processing, Data Pipelines, Amazon Redshift - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25303_e4b67e2f634089028499047b4f04b77e ## About the Role * 8+ years of experience building well-tested, API-driven applications and services that run at scale in production. * Track record of building scalable, high-performance distributed systems. * Strong experience with streaming data systems (Kafka, Flink, Pulsar) and/or orchestration platforms (Airflow, Dagster, Temporal), especially at the platform layer. * Hands-on experience designing and operating stateful, real-time data pipelines at scale (checkpointing, state management, watermarking). * Experience evaluating architectural trade-offs in data processing and orchestration systems. * Experience building multi-tenant or end-to-end data infrastructure that supports multiple teams or production use cases. * Expertise in managing cloud data stores (Snowflake, BigQuery, Redshift, etc.) and data lake architectures (AWS S3) for processing and serving data products. * Strong experience supporting operational systems to ensure uptime, reliability, and maintainability (monitoring, alerting, incident management). * Familiarity with DevOps/SRE practices and CI/CD tooling (GitHub, GitHub Actions). * Understanding of data governance and compliance principles (access controls, retention policies, auditability)., * Experience managing cloud technologies (AWS or Google Cloud) and comfort with infrastructure-as-code (e.g., Terraform). * Proficiency in at least one server-side programming language (preferably Python), common algorithms and data structures, and software design principles. * Self-starter ethic, thriving under high autonomy. * Exceptional interpersonal and communication skills. ## Description * Define technical direction and lead development of critical data platform systems that power next-generation capabilities at Whatnot. * Lead the buildout and evolution of our data orchestration and streaming platforms, moving them from early investment to production-ready usage company-wide. * Design scalable, reliable, multi-tenant data infrastructure rather than simply building pipelines on an existing platform. * Own core platform concerns including scalability, performance, reliability, SLOs, and operational excellence for data processing systems. * Build high-quality systems that support real-time analytics, event-driven applications, and machine-learning infrastructure needs across Whatnot. * Make key decisions about how data systems should be integrated across Whatnot, and partner cross-functionally to bring that architecture to life. * Collaborate closely with engineering partners across product, platform, machine-learning, and data to enable fast, safe, and scalable development. * Help shape broader company architecture across orchestration, stream processing, real-time systems, analytics, and content understanding. * Apply DevOps/SRE practices, including CI/CD, infrastructure automation, monitoring, and incident response, to keep platform systems reliable at scale. * Help define and enforce data governance and compliance standards across our data lake and downstream systems.