Senior Analytics Engineer: Architect Trusted Data for AI

Render; San Francisco (CA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Paid vacation 2026+

Parental leave 14 weeks

Disability & life insurance

Medical coverage 100%

Dental/vision coverage for dependents

Lifestyle stipend

Cell phone/internet subsidy

Commuter benefits (Bay Area)

Home office stipend

Job summary

Render is hiring a Senior/Staff Analytics Engineer to lead the Analytics Engineering platform. You will partner with analysts, data scientists, and product teams to translate domain knowledge into scalable data models and semantic layers for trusted metrics and AI-assisted analyses.

You will own the architecture, establish standards, and mentor teams to improve data quality, performance, and developer experience across the data stack.

Qualifications

• 7+ years in Analytics Engineering or Data Engineering
• Hands-on dbt production experience (≥3 years)
• Expert SQL and dimensional modeling (Kimball)
• Experience building semantic/context layers for self-service analytics
• Strong communication across technical and non-technical stakeholders

Responsibilities

• Own our Analytics Engineering architecture and guide long-term evolution of the platform
• Build trusted, reusable data models (dbt) for metrics across teams
• Establish engineering standards for data modeling, testing, docs, version control, CI/CD
• Enable self-service analytics by designing semantic/context layers for humans and AI
• Partner with analysts/scientists to translate domain logic into scalable warehouse models
• Improve reliability and efficiency with data quality and cost-aware warehouse design
• Mentor analysts and engineers on dbt, dimensional modeling, and best practices

Skills

SQL proficiency

Data modeling

Communication

Mentoring

Self-service analytics

Tools

dbt

BigQuery

Databricks

Snowflake

CI/CD

Git

Job description

Render is hiring a Senior/Staff Analytics Engineer to lead the Analytics Engineering platform. You will partner with analysts, data scientists, and product teams to translate domain knowledge into scalable data models and semantic layers for trusted metrics and AI-assisted analyses.

You will own the architecture, establish standards, and mentor teams to improve data quality, performance, and developer experience across the data stack.