Senior/Staff Data Engineer

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.

Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users.

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.

We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you.

Applying to Render

We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team.

We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed.

Our interview process is unique to each role, and we value the candidate experience just as much as our customer experience. We hope your conversations with us reflect a thoughtful process that is illuminative, enjoyable, and respectful of your time.

About the Role

We're looking for a Senior/Staff Data Engineer to join our growing Data team and set the technical direction for the systems that power analytics, data science, and operational decision-making across Render. As we scale, you'll build and operate the pipelines, services, and infrastructure that make our data accurate, timely, and trusted.

In this role, you'll work across the modern data stack, software and platform engineering, and emerging AI and agent workflows. You'll partner closely with analytics engineers, analysts, scientists, engineering teams, and business stakeholders to translate evolving needs into reliable, maintainable data systems.

As a Senior/Staff-level individual contributor, you'll be a hands-on technical leader—shaping architecture and the platform roadmap, mentoring data engineers, and raising the bar for how we design, build, and operate our infrastructure. The systems and standards you establish will help teams across Render understand the business, make better decisions, and bring new data science, analytics, and AI capabilities into production.

What You'll Do

Own our Data Platform Engineering architecture. 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.

Build and operate trusted data pipelines. Develop ingestion services, integrations, and pipelines that deliver accurate, timely data. Make testing, logging, alerting, and observability part of how we build and operate the platform.

Evolve our orchestration platform. Own workflow execution, worker infrastructure, upgrades, and operational reliability. Improve deployment patterns and balance performance, cost, and maintenance needs as workloads grow.

Own warehouse reliability, performance, and access. Improve our BigQuery environment, including query performance, cost efficiency, permissions tooling, and governance. Partner with Analytics Engineering on warehouse architecture and the foundations that support scalable dbt models.

Build cloud services and infrastructure. Develop APIs, event-driven ingestion, and reusable services that connect our data systems. Use infrastructure as code to create maintainable infrastructure, reusable modules, and predictable deployments.

Establish engineering standards. Improve version control, CI/CD, testing, documentation, and operational practices across the Data Platform. Reduce technical debt and help the team make sound decisions about tooling and platform evolution.

Partner across teams. Work with analytics engineers, analysts, scientists, Engineering, IT, and business teams to clarify requirements, validate outputs, and communicate risks, tradeoffs, and timelines. Collaborate with IT and Security on secure access and data handling.

Support data science, analytics, and AI workflows. Prepare model-ready datasets, make features available to downstream systems, and help integrate AI and LLM workflows into production.

Grow the team’s technical capabilities. Mentor data engineers through code review, pairing, design feedback, and coaching, and help engineers take ownership of increasingly complex systems.

What We're Looking For

7+ years of experience in Analytics Engineering, Data Engineering, or a related technical field, with a track record of setting direction, driving architecture, and delivering complex data systems across a team.

Deep expertise in modern cloud data warehouses such as BigQuery, Databricks, or Snowflake, including data modeling, query performance, cost management, and access control.

Strong Python and SQL skills, with hands-on experience building reliable ingestion and ELT pipelines and maintainable data models.

Experience operating orchestration platforms such as Prefect, Airflow, or Dagster, including responsibility for deployments, upgrades, workers, and operational reliability.

Hands-on experience with cloud infrastructure and infrastructure as code, using Terraform or equivalent tools to build predictable, maintainable systems.

Experience building cloud applications or backend services, including APIs, ingestion services, and event-driven workflows.

Strong production engineering practices, including testing, logging, alerting, observability, version control, and CI/CD.

A track record of mentoring engineers through coaching, code review, pairing, and design feedback.

Excellent communication and cross-functional collaboration skills. You can explain technical tradeoffs, build alignment across data, engineering, and business teams, and lead through influence.

Experience using AI-assisted development tools such as Codex, Cursor, or Claude Code to accelerate delivery while maintaining a high bar for correctness and maintainability.

Nice-to-Haves

Hands-on experience with Render’s data stack, including GCP, BigQuery, Segment, and dbt.