Senior Software Engineer, Content Ingestion

What You’ll Do

• Design, build, and maintain high-throughput data pipelines that ingest and transform large volumes of unstructured content into structured and enriched datasets
• Contribute to the design and evolution of ingestion systems, improving scalability, reliability, and maintainability over time
• Improve data quality, correctness, and enrichment workflows to support downstream systems such as Search and Data Science
• Build and operate distributed, event-driven systems and streaming pipelines with strong observability and fault tolerance
• Partner cross-functionally with Product, Data Science, Search, and Platform teams to deliver high-quality data that powers customer-facing features
• Take ownership of projects end-to-end, balancing speed of delivery with system reliability and long-term maintainability
• Support and mentor teammates through code reviews, technical discussions, and knowledge sharing

To Be Set Up for Success in This Role, You’ll Need to Have

• ~5–8 years of professional experience as a software engineer
• Experience designing, building, and operating distributed systems, data pipelines, or event-driven architectures
• Strong proficiency in Python or a similar backend programming language
• Experience building and maintaining reliable, observable, and scalable services or microservices
• Experience working with streaming technologies such as Kafka, Kinesis, or similar systems
• Experience with APIs and service communication patterns such as gRPC and Protocol Buffers
• Experience working with large-scale data systems or high-throughput SaaS platforms
• Familiarity with relational or search databases such as MySQL, Postgres, Elasticsearch, or OpenSearch
• Ability to make thoughtful technical tradeoffs related to performance, reliability, and maintainability

If Any of the Below Also Describe You, This Could Be an Exciting Opportunity

• Experience working on content ingestion, ETL/ELT, or data enrichment pipelines
• Experience improving throughput, reliability, and observability in large-scale data systems
• Experience with background job processing frameworks and asynchronous workflows
• Experience working with high-volume event streams or large datasets