Principal Data Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Principal Data Engineer (AI): Designing and architecting a next-generation data platform capable of serving both human users and AI agents with an accent on semantic layers, query engines, and data discoverability. Focus on transitioning from Athena to ClickHouse and building a foundation for agentic AI consumption.
Location: Remote within the ANZ Region (Australia/New Zealand)
Company
provides a high-scale CI/CD platform used by some of the world's most advanced engineering teams to ship software.
What you will do
- Own the end-to-end data architecture strategy, technical decision-making, and foundational patterns.
- Design and implement a data platform optimized for both human users and AI agents.
- Select and implement the technology stack, including query engines, semantic layers, ingestion, and streaming.
- Optimize system performance and eliminate bottlenecks through hands-on technical work.
- Serve as the definitive technical voice for data across the entire engineering organization.
Requirements
- Proven track record of owning and leading data architecture at scale in production environments.
- Deep expertise in the modern data stack, including headless-BI/semantic layers and analytical stores.
- Experience with or strong drive to solve challenges related to how agentic AI consumes data.
- Ability to operate with high autonomy in a remote, asynchronous work environment.
- Must be based in the ANZ Region.
Nice to have
- Experience working with developer tools or CI/CD platforms.
- Comfortability working within a Ruby monolith environment.
- Technical knowledge of Kafka or Flink.
- Experience building with privacy and compliance requirements in mind.
Culture & Benefits
- High-autonomy, flat organization where individual contribution drives influence.
- Remote-first culture since 2013, specifically designed for async work and deep focus.
- Opportunity to work on frontier problems at the intersection of data platforms and AI.
- Direct impact on infrastructure supporting some of the largest engineering teams globally.
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