Principal Software Engineer, Data
Hybrid
Posted 10d ago
Remote Work Policy
On-site
Categories
Applied AI Engineer
About the job
Cloudflare is seeking an experienced, product-minded Principal Software Engineer to join the Town Lake team. This team is responsible for making vast amounts of data accessible and valuable across the company, building a modern, agentic-first data lakehouse platform. You will play a key role in taking this fast-growing internal platform to become the foundational data infrastructure for the entire company. This is a high-impact, high-visibility role where you will lead technical architecture and drive implementation for critical services, leveraging AI deeply to accelerate development and create innovative solutions. If you are a builder who thrives on solving complex problems and shaping the future of data platforms, this opportunity is for you.
Responsibilities
- Define, design, and execute strategic technical architecture for highly visible and critical data infrastructure.
- Lead the design and development of tools and infrastructure to scale data infrastructure.
- Lead the design and development of data pipelines and data products, including automation tools.
- Become a subject matter expert on data platforms, tools, and data itself to guide stakeholders.
- Work across the tech stack, including Kubernetes, Trino, Iceberg, Clickhouse, and PostgreSQL.
- Mentor and support junior engineers, fostering a culture of exceptional delivery and accountability.
Requirements
- 8+ years of experience as a software engineer with a focus on designing, building, and scaling data infrastructure.
- Proven experience leading technical initiatives in a cross-functional context with multiple stakeholders.
- Extensive experience with data infrastructure at scale, including tools like Trino, Spark, Iceberg/Delta Lake, Kafka, Clickhouse, PostgreSQL.
- Experience designing, building, and debugging data pipelines at scale.
- Proficiency in backend languages like Go, Python, Typescript, and Rust, along with SQL.
- Excellent analytical skills with a focus on understanding data usage and driving value.
- Strong communication skills, particularly in articulating technical concepts to both technical and non-technical audiences.