Software Engineer, Data Foundations

Whatnot is a live shopping platform for buying, selling, and discovering products across categories. The Software Engineer, Data Foundations will lead the technical direction and development of scalable data orchestration, streaming, and infrastructure systems supporting real-time analytics, event-driven applications, and machine learning. The role also focuses on reliability, operational excellence, cross-functional architecture, and data governance.

Responsibilities:

• 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, helping drive them from early platform investment to production-ready usage across the company
• Design scalable, reliable, multi-tenant data infrastructure rather than simply building pipelines on top of 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 then 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

Requirements:

• As our next Software Engineer, Data Foundations, you should have 8+ years of experience, plus:
• Ability to write 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 (e.g., Kafka, Flink, or Pulsar) and/or orchestration platforms (e.g., Airflow, Dagster, or Temporal), with particular strength in building or evolving the platform layer itself, not just downstream pipelines
• Hands-on experience designing and operating stateful, real-time data pipelines at scale, including concepts like checkpointing, state management, and watermarking
• Experience evaluating architectural tradeoffs in data processing and orchestration systems, including when a given tool is the right solution and when it is not
• 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 (e.g., AWS S3) for processing and serving data products
• Strong experience supporting operational systems to ensure uptime, reliability, and maintainability, including monitoring, alerting, and incident management
• Familiarity with DevOps/SRE practices and CI/CD tooling, including GitHub and GitHub Actions
• Understanding of data governance and compliance principles (e.g., data access controls, retention policies, auditability)
• Experience managing cloud technologies (AWS or Google Cloud) and comfort with infrastructure-as-code approaches (for example, Terraform)
• Proficiency in at least one server-side programming language (preferably Python), common algorithms and data structures, and software design principles
• Self-starter ethic, with the ability to thrive under a high level of autonomy
• Exceptional interpersonal and communication skills