Render is the fastest way for developers to run applications in production.

Render

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data-scientist

Render is a modern cloud platform for developers and teams that simplifies the process of building, deploying, and scaling applications. It offers a range of services including web services, static sites, cron jobs, background workers, PostgreSQL databases, and Redis management. Render's platform is designed for ease of use with features such as automatic deployments, load-based autoscaling, and infrastructure as code. It also provides robust security measures like DDoS protection and data privacy compliance. Render caters to a wide range of development stacks with support for various programming languages and Docker images, providing developers with a seamless environment to manage and scale their infrastructure. With a focus on speed, reliability, and collaboration, Render helps developers efficiently manage their applications and infrastructure from development to production.

• Serve as a strategic analytics partner to leaders and cross-functional partners across Product, Engineering, Growth, Go-to-Market, Finance, and other teams.
• Identify high-impact questions, frame decisions, and determine how success should be measured.
• Define KPIs and measurement frameworks for acquisition, activation, adoption, engagement, retention, conversion, expansion, and customer outcomes.
• Surface patterns across users, customers, products, and the business.
• Identify opportunities, diagnose friction, and help determine investments and priorities.
• Design and analyze experiments, develop guardrail metrics, and evaluate initiatives.
• Define instrumentation and measurement plans for new products, programs, and initiatives.
• Build and maintain dbt models, semantic layers, and context layers with Analytics Engineering.
• Transform behavioral and business data into reliable datasets supporting decision-making across Render.
• Establish analytical best practices and improve data-driven decision-making.
• Mentor scientists and cross-functional partners on measurement, experimentation, and data literacy.
• Explore AI-assisted tools to make analytics faster and more accessible while maintaining accuracy and analytical judgment.

Senior/Staff Data Scientist

Senior/Staff Data Scientist shaping metrics, experimentation, and analytics foundations for Render’s developer cloud platform. Partnering across product and business teams to drive data-informed decisions.

analytics-engineer

• Lead the evolution of Render’s Analytics Engineering platform
• Design, build, and maintain governed dbt models as authoritative sources for business-critical metrics
• Define and improve data modeling, testing, documentation, version control, CI/CD, and code review practices
• Review high-impact dbt changes and reduce technical debt across the analytics codebase
• Design and maintain semantic and context layers for consistent metrics, data discovery, and reliable analysis by people and AI tools
• Partner with analysts, scientists, data engineers, and teams across Product, Engineering, Growth, Go-to-Market, Finance, and other business functions
• Translate domain-specific business logic into scalable, maintainable warehouse models
• Partner with Data Engineering to improve source data quality, warehouse architecture, BigQuery performance, and cost efficiency
• Mentor analysts, scientists, and analytics engineers on dbt development, dimensional modeling, and engineering best practices
• Set technical direction and shared standards for Analytics Engineering at Render

Senior/Staff Analytics Engineer

Staff Analytics Engineer leading analytics architecture, dbt models, and semantic layers at Render. Building trusted data foundations for AI-assisted decision-making across the developer cloud platform.

data-engineer

• Set technical direction for core data systems, lead design decisions, and deliver reliable production systems
• Partner with Data team leadership to shape the platform roadmap and evaluate architectural and build-versus-buy tradeoffs
• Develop ingestion services, integrations, and pipelines that deliver accurate, timely data
• Implement testing, logging, alerting, and observability across the platform
• Own workflow execution, worker infrastructure, upgrades, and operational reliability for the orchestration platform
• Improve deployment patterns while balancing performance, cost, and maintenance needs
• Improve the BigQuery environment, including query performance, cost efficiency, permissions tooling, and governance
• Partner with Analytics Engineering on warehouse architecture and scalable dbt model foundations
• Develop APIs, event-driven ingestion, and reusable cloud services
• Use infrastructure as code to create maintainable infrastructure, reusable modules, and predictable deployments
• Improve version control, CI/CD, testing, documentation, and operational practices across the Data Platform
• Collaborate with analytics engineers, analysts, scientists, Engineering, IT, Security, and business teams
• Prepare model-ready datasets, make features available to downstream systems, and integrate AI and LLM workflows into production
• Mentor data engineers through code review, pairing, design feedback, and coaching

Senior/Staff Data Engineer

Staff Data Engineer shaping Render’s cloud data platform for AI-native applications. Building reliable pipelines, BigQuery infrastructure, orchestration, and production AI workflows.

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Senior/Staff Data Scientist

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Senior/Staff Analytics Engineer

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Senior/Staff Data Engineer

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