Staff Software Engineer - Ingestion Platform

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com.

Who We Are:

The Infrastructure organization enables Reddit to deliver reliability, performance, and efficiency with a single opinionated technology stack. The Ingestion Platform team within Infrastructure builds a low-code interface for moving data from supported sources to supported sinks, making it easier for teams across Reddit to create reliable, scalable data pipelines without building and operating bespoke infrastructure. Our platform supports streaming and batch data movement from Kafka to destinations such as BigQuery and object storage, and is expanding toward S3/GCS, Apache Iceberg, transformations, deduplication, and additional sinks. We work closely with Data Pipelines, Data Movement, Ads Data Platform, ML Indexing, Flink Platform, Storage, and other partner teams to improve developer velocity, reliability, observability, and operational efficiency.

We are looking to hire a Staff Software Engineer to help shape and scale this platform. This is a high-impact role where your technical judgment, customer empathy, and operational mindset will influence the future direction of data movement at Reddit.

What You’ll Do:
As a Staff Engineer, you will lead the development and evolution of Reddit’s Ingestion Platform.

• Design, write, and deliver reliable software for distributed data movement across streaming and batch workloads, with a focus on availability, scalability, latency, correctness, and cost efficiency.
• Own the architecture and evolution of the platform’s control plane and data plane, including pipeline APIs, controllers, connectors, target managers, schemas, and sink integrations.
• Expand the platform beyond Kafka-to-BigQuery by helping deliver production-ready paths to S3/GCS and Apache Iceberg, as well as transformations, deduplication, dead-letter queues, and other reusable capabilities.
• Build high-quality connectors and abstractions for systems such as Kafka, BigQuery, S3, GCS, Iceberg, Flink, and other data stores, while keeping the platform modular and easy to extend.
• Improve the self-service experience for platform users through clear APIs, safe defaults, automated provisioning, documentation, onboarding workflows, and actionable observability and alerting.
• Lead migrations from bespoke and legacy ingestion systems to the Ingestion Platform, partnering with teams such as Ads Data Platform and ML Indexing to make migrations safe, incremental, and low-touch.
• Establish strong reliability, security, and operational practices for pipelines running across Kubernetes clusters, including schema evolution, workload identity, permissions, deployment safety, monitoring, and incident response.
• Identify gaps in the platform’s architecture and product experience, and lead redesigns that improve developer velocity and enable Reddit’s continued growth.
• Work collaboratively with engineers and stakeholders across Infrastructure, Data Platform, Product, Ads, ML, Storage, and partner teams to align roadmaps and deliver durable solutions.
• Mentor and guide backend and data infrastructure engineers across the company, raising the bar for technical design, operational excellence, and customer focus.

Who You Might Be:

• 10+ years of hands-on experience building internet-scale distributed systems, data infrastructure, or platforms used by other developers.
• BS, MS, PhD in Computer Science, a related field, or equivalent practical experience.
• Strong software development experience in one or more general-purpose languages such as Go, Python, Java, or Scala.
• Deep experience designing and operating high-throughput, fault-tolerant data pipelines or platform services, including streaming and batch processing.
• Experience with data movement patterns and systems such as Kafka, BigQuery, S3, GCS, Apache Iceberg, Flink, or comparable technologies.
• Experience designing APIs and platform abstractions, including schema evolution, serialization formats such as Protocol Buffers, and service-to-service communication such as gRPC.
• Familiarity with Kubernetes and cloud-native platform concepts, including controllers, custom resources, workload identity, infrastructure automation, and multi-cluster deployments.
• A strong understanding of observability and operational excellence: metrics, logging, alerting, SLOs, incident response, data quality, and safe migration practices.
• A product-minded engineer who advocates for platform users and can turn ambiguous customer and partner needs into simple, reliable, and scalable solutions.
• Demonstrated…