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 Content Platform team within Infrastructure additionally focuses on empowering product teams to build the best possible Content-related experiences, easily and reliably. This is a high-impact team that owns the Tier-0 services and core data models that power some of the most visible aspects of our product - viewing a feed, posting, commenting, upvoting - and we work closely with teams like Consumer, Ads, Feeds, Storage and Ranking. This team is also responsible for running and maintaining R2 – Reddit’s monolith legacy stack that is pretty much in the critical path for every Critical User Journey at Reddit.

We are looking to hire a Staff Software Engineer to help us in this mission. This is a high impact role where your unique insights into improving our operational posture as well as harmonizing feedback from customers will shape the future direction of our platform.

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.