The opportunity
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…
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.
What they're looking for
- + 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.
