Data Engineer

Summary

11x is building AI workers and the data infrastructure that enables them to serve customers. The Data Engineer will own and extend customer data ingestion, pipelines, synchronization systems, retrieval layers, and foundational infrastructure supporting AI products and workflows. The role also partners with product and engineering teams to improve reliability, scalability, and AI capabilities.

Responsibilities

• Own and extend our customer data ingestion platform
• Build and maintain large-scale data pipelines powering AI products and customer workflows
• Design systems for syncing customer data across external platforms, CRMs, and third-party systems
• Help architect our future data lake, retrieval layer, and data infrastructure strategy
• Build ingestion and querying systems for lead, account, enrichment, and customer knowledge data
• Create the infrastructure that gives our AI workers access to the information they need to reason, act, and improve over time
• Partner closely with product and engineering teams to unlock new AI product capabilities
• Improve reliability, observability, performance, and scalability across our data stack
• Contribute across backend systems and infrastructure, not just traditional data engineering projects
• Push ideas into production quickly instead of over-optimizing in planning phases

Skills

• 4+ years of software engineering or data engineering experience
• Strong experience building and maintaining production-grade data systems and pipelines
• Experience with Python and Typescript
• Strong backend engineering fundamentals beyond traditional data engineering
• High agency — you naturally move things forward without waiting for direction
• Comfort operating in ambiguity and building without a playbook
• Strong systems thinking and architectural intuition
• Ability to balance speed with long-term scalability
• Strong problem-solving skills and a willingness to own problems end-to-end
• Hungry to grow. You want expanding scope, responsibility, and ownership over time
• Excitement about AI-native workflows and the future of software development
• Experience with ClickHouse or other columnar databases
• Experience building customer data platforms (CDPs)
• Experience with Airbyte or similar data integration and ingestion platforms
• Experience with CRM integrations and synchronization systems
• Experience designing data lake architecture
• Experience supporting AI or ML products
• You've used tools like Claude Code, Codex, Cursor, or similar heavily in your workflow
• You care deeply about engineering velocity and iteration speed

Qualifications

Must Haves

• 4+ years of software engineering or data engineering experience
• Strong experience building and maintaining production-grade data systems and pipelines
• Experience with Python and Typescript
• Strong backend engineering fundamentals beyond traditional data engineering
• High agency — you naturally move things forward without waiting for direction
• Comfort operating in ambiguity and building without a playbook
• Strong systems thinking and architectural intuition
• Ability to balance speed with long-term scalability
• Strong problem-solving skills and a willingness to own problems end-to-end
• Hungry to grow. You want expanding scope, responsibility, and ownership over time
• Excitement about AI-native workflows and the future of software development

Nice to Haves

• Experience with ClickHouse or other columnar databases
• Experience building customer data platforms (CDPs)
• Experience with Airbyte or similar data integration and ingestion platforms
• Experience with CRM integrations and synchronization systems
• Experience designing data lake architecture
• Experience supporting AI or ML products
• You've used tools like Claude Code, Codex, Cursor, or similar heavily in your workflow
• You care deeply about engineering velocity and iteration speed