Senior Data Engineer

LiveKit is building the infrastructure layer for the voice-driven era of computing, powering voice AI applications for major companies. As a Senior Data Engineer, you will own the analytics infrastructure and design scalable GCP-based data pipelines, ensuring reliable and cost-effective solutions while collaborating with the analytics team.

Responsibilities:

• Own the Analytics Infrastructure: You are the end-to-end owner of our GCP-based data infrastructure — including ingestion, movement, storage, security, and availability. You build and operate reliable, scalable pipelines that power analytics, and partner closely with the Analytics team on downstream transformation and BI
• Maximize the Cloud Ecosystem: Build cost-effective solutions primarily within GCP-native services, while bringing transferable cloud infrastructure expertise. Know when to extend with third-party tooling or homegrown solutions, and make pragmatic tradeoffs
• Contribute Across Data Infrastructure: While analytics is the primary focus, you'll bring broad data pipeline expertise to application data needs in collaboration with the product engineering team
• Managed Services First: Favor managed solutions over self-hosting. Evaluate build vs. buy with cost and operational burden in mind
• Engineering Standards: This role reports to the Head of Data within the Engineering org. Expect PR reviews, automated testing, proper change management, and production-grade standards
• AI-First Development: Work extensively with AI coding assistants and contribute to evolving our AI development workflows and infrastructure
• Startup Pace: Priorities shift quickly. Balance long-term architectural thinking with the tactical execution the moment requires

Requirements:

• 8+ years of experience in data engineering with strong Python and SQL expertise
• You've built analytics data infrastructure from scratch — ideally more than once — and owned the architecture end-to-end
• Experience with cloud-native data infrastructure (GCP preferred; strong AWS builders who can translate cloud concepts welcome)
• Familiarity with BigQuery, Dataflow, Cloud Storage, or equivalent services
• Proven ability to design and implement production-grade data pipelines and aggregation layers for BI and analysis
• AI-first development mindset with hands-on experience building AI-driven workflows and effectively using AI coding assistants
• Strong understanding of data modeling, transformation patterns, and working with dbt
• Experience with data movement tools (Estuary, Airbyte, Fivetran, or similar)
• Solid infrastructure and DevOps fundamentals: Terraform or similar IaC, CI/CD, Git workflows, and change management
• Experience implementing observability and monitoring for data systems (DataDog, Grafana, or similar)
• Strong communication skills and ability to work cross-functionally with engineering and business stakeholders
• Self-directed and comfortable with ambiguity in a fast-paced startup environment
• Located in the US or Canada
• Experience coordinating with dbt and analytics engineering teams
• Background with AI workflow tools (n8n or similar)
• Background with AI coding assistants
• Prior experience as an early infrastructure hire building from the ground up
• Prior experience building on GCP/BigQuery in production