Senior/Staff Analytics Engineer - Render

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure.

Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers.

Our platform is trusted by over 7 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $260M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development.

About the Role

We're looking for a Staff Analytics Engineer to join our growing Data team and lead the evolution of our Analytics Engineering platform. As Render scales, you'll build the foundations that turn raw data into trusted, reusable models for analytics, executive reporting, and AI-assisted decision-making.

In this role, you'll partner closely with analysts, scientists, data engineers, and teams across Product, Engineering, Growth, Go-to-Market, Finance, and other business functions. Analysts and scientists will bring domain expertise and own business logic within their areas; you'll own the technical architecture, modeling standards, and engineering practices that help that work scale reliably.

As a Staff-level individual contributor, you'll set the technical direction for Analytics Engineering at Render—strengthening data quality, improving the developer experience, and building semantic and context layers that make data easier to discover and use.

What You'll Do

• Own our Analytics Engineering architecture: Guide the long-term evolution of Render’s Analytics Engineering platform, strengthening foundational models so data remains trusted, scalable, and ready for AI-assisted analytics.
• Build trusted, reusable data models: Design, build, and maintain governed dbt models that serve as authoritative sources for business-critical metrics across Product, Engineering, Growth, Go-to-Market, Finance, and other teams.
• Establish engineering standards: Define and improve practices for data modeling, testing, documentation, version control, CI/CD, and code review. Review high-impact dbt changes and reduce technical debt across the analytics codebase.
• Enable self-service and AI-assisted analytics: Design and maintain semantic and context layers that make metrics consistent, data discoverable, and analysis reliable for both people and AI tools.
• Partner closely with analysts and scientists: Help analysts and scientists translate domain-specific business logic into scalable, maintainable warehouse models, moving shared logic out of individual reports and into governed datasets.
• Improve reliability and efficiency: Partner with Data Engineering to strengthen source data quality, warehouse architecture, and BigQuery performance and cost efficiency.
• Raise the bar for Analytics Engineering: Mentor analysts, scientists, and analytics engineers on dbt development, dimensional modeling, and engineering best practices.

What We're Looking For

• 7+ years of experience in Analytics Engineering, Data Engineering, or a related technical field, including at least 3 years of hands-on experience running dbt in production.
• Expert-level SQL skills and a track record of designing and owning scalable Kimball dimensional models.
• Deep expertise in modern Analytics Engineering practices, including Git, testing, CI/CD, documentation, data contracts, lineage, and governance.
• Experience building semantic and context layers, trusted metrics, and warehouse architectures that support self-service analytics for humans and AI agents.
• Strong understanding of modern cloud data warehouse architecture, performance optimization, and cost efficiency (BigQuery, Databricks, or Snowflake).
• Proven track record of establishing technical standards, influencing engineering practices without formal authority, and reducing technical debt.
• Demonstrated ability to partner with analysts, scientists, and cross-functional stakeholders to translate requirements into maintainable models.
• Excellent communication skills to explain complex technical tradeoffs across technical and non-technical audiences.
• Experience building data models connecting product usage, acquisition, CRM, and financial data across the customer lifecycle.
• Experience utilizing AI-assisted coding or analytics tools (e.g., Codex, Cursor, Claude Code) to accelerate data workflows.

Nice-to-Haves

• Hands-on experience with Render’s analytics stack (BigQuery, Segment, dbt, Metabase, Mixpanel).
• Experience with developer-focused, product-led, sales-led, or usage-based business models.
• Knowledge of cloud infrastructure, PaaS, developer tooling, or technically complex developer products.

Benefits

• 4 weeks of paid vacation.
• 14 weeks of fully paid parental leave for all parents.
• 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent (FSAs and HSAs available).
• 401(k) plan, long-term disability, and life insurance.
• Monthly lifestyle stipend for wellness, mental health, therapy, and hobbies.
• Monthly cell phone and internet subsidy.
• Commuter benefits for Bay Area team members; home office stipends for remote team members.
• Continuous learning benefits and development support.