Analytics Engineer

• Build and ship internal web tools and dashboards on top of existing Zoox data sources, from prototype through production use
• Work with TPMs and engineering partners to turn business questions into scoped tools and iterate based on feedback
• Design queries, transformations, and pipelines to keep data current without manual intervention
• Extend geospatial tooling with new attributes, data sources, and visualizations to inform service expansion
• Surface data coverage gaps, flag low-confidence results, and make tool assumptions visible
• Partner with leaders across vehicle development, software engineering, manufacturing, fleet operations, and business functions to support corporate milestones
• Own a piece of the stack end to end and deliver tools for program and executive reviews

Program Tooling & Analytics Developer

• Investigate individual incidents and requests end-to-end using raw production data and systems to determine root cause and recommend resolution
• Build and maintain metrics measuring system health and performance over time using statistical methods
• Produce clear descriptive reporting for stakeholders
• Contribute to the team's core framework and tooling to make investigation and measurement more repeatable
• Operate independently on ambiguous, partially-scoped problems
• Identify and collaborate with data science, engineering, and trading partners when problems cross team boundaries
• Work with real-time, event-driven data to reconstruct and explain system behavior during live events

• Develop, research, and implement data analysis projects, including data reporting, data visualizations, data design, and ad-hoc research projects
• Develop and implement data visualizations using Tableau
• Understand business processes and identify pain points where enhanced reporting and analytics can add value
• Perform complex data analyses to derive actionable insights
• Ensure data accuracy, consistency, and completeness
• Use storytelling techniques to transform complex analyses into compelling narratives
• Collaborate with stakeholders to define detailed data project requirements aligned with business objectives
• Communicate findings through presentations and detailed reports
• Advocate for dashboard adoption in data-driven decision-making and strategic planning
• Work with firm management, senior management, and departments to optimize reporting tools
• Protect and maintain highly sensitive, confidential, privileged, financial, and proprietary information

Senior Data Solutions 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 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 Senior/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. You'll help teams move faster with consistent metrics and maintainable models they can trust.




WHAT YOU'LL DO

 - Own our Analytics Engineering architecture. Guide the long-term evolution of Render’s Analytics Engineering platform, strengthening foundational models so our 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 dashboards 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, and help teams adopt shared standards.




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 across multiple business domains.

 - Strong understanding of modern cloud data warehouse architecture, performance optimization, and cost efficiency, with experience in platforms such as BigQuery, Databricks, or Snowflake.

 - A track record of establishing technical standards, influencing engineering practices without formal authority, and improving reliability while reducing technical debt.

 - Proven ability to partner closely with analysts, scientists, and business stakeholders to translate requirements into scalable, maintainable data models.

 - Excellent communication skills. You can explain complex technical concepts and tradeoffs to technical and non-technical audiences and build alignment across teams.

 - Experience building data models that connect product usage, acquisition, CRM, and financial data across the customer lifecycle.

 - Experience using AI-assisted coding or analytics tools such as Codex, Cursor, or Claude Code to accelerate data modeling, testing, documentation, or exploration.




NICE-TO-HAVES

 - Hands-on experience with Render’s analytics stack, including BigQuery, Segment, dbt, and analytics tools such as Metabase or Mixpanel.

 - Experience with developer-focused, product-led, sales-led, or usage-based businesses.

 - Knowledge of cloud infrastructure, PaaS, developer tooling, or other technically complex products.

If this role excites you but you don’t meet every single requirement, we’d still love to hear from you—your unique experience might be just what we need.




BENEFITS

 - 4 weeks of paid vacation.

 - 14 weeks of fully paid parental leave for all parents to bond with a newly born, adopted, or fostered child. We will also work with you to create a supportive plan of return.

 - Long-term disability, life insurance, and 401K plans.

 - 100% employer-paid medical coverage and 99% employer-paid dental and vision coverage for you and a dependent. FSAs and HSAs are available as well.

 - Monthly lifestyle stipend for wellness, mental health and therapy, hobbies, etc.

 - Monthly cell phone and internet subsidy.

 - Commuter benefits for Renders in the Bay Area, and home office stipends for remote Renders.

 - Continuous learning benefits & related support.

This position is generally not eligible for new visa sponsorship. At Render's discretion, the business may sponsor existing visa transfers. Applicants who require sponsorship must receive business authorization.

Render is an equal-opportunity employer. We know that employing a team rich in diverse thoughts, experiences, and opinions allows our employees, product, and community to flourish. We make all employment decisions including hiring, evaluation, termination, promotional, and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

We encourage all who are interested to apply. We can't wait to hear from you!

Render — CCPA Applicant Privacy Notice https://drive.google.com/file/d/1wKr9IejoT5McFrs9I2mahQnf6AFwb3z2/view

Render — GDPR Applicant Privacy Notice https://drive.google.com/file/d/1_8jtyXQ1HdRdTdQn9sZ7n-R-zAGBmsFa/view

Senior/Staff Analytics Engineer

• Run the analytics database and scheduled jobs, ensuring they are reliable, monitored, and documented
• Pull in new sources through vendor APIs, including CRM, contact center, and lending platforms, using incremental, restartable loads
• Model raw data into trusted tables and views
• Build operational reporting, including call lists, merchant partner reporting, and management reports
• Own the data dictionary and KPI definitions in partnership with business owners
• Lead one analyst, setting direction and improving quality
• Learn the business and current platform during the first 90 days
• Take over daily platform operations alongside the team
• Deliver one new data source end to end
• Establish and document shared KPI definitions

Lead Analytics Engineer

• Design, develop, test, deploy, and maintain complex data structures, enterprise reports, dashboards, analytical systems, and software
• Lead analysis of contact center, IVR, digital, cloud, customer, workforce, and operational data
• Identify root causes, quantify business impact, and recommend practical actions
• Build, enhance, and troubleshoot reporting and monitoring solutions
• Monitor data patterns, anomalies, customer contact behavior, IVR performance, containment, transfers, service levels, handle time, and other operational indicators
• Partner with operations, workforce management, IVR, automation, product, engineering, data architecture, data science, and governance teams
• Research and query internal and external, structured and unstructured data sources
• Expand reporting capabilities, improve data availability, and strengthen business intelligence solutions
• Assess opportunities for business intelligence, automation, self-service improvement, and proactive performance management
• Improve development practices, reporting standards, metric definitions, documentation, validation routines, governance controls, and data stewardship
• Protect sensitive data and support data classification and access controls
• Instruct, review, and coach junior Data Analytics Engineers
• Communicate complex insights to technical and non-technical stakeholders using data storytelling

Senior Contact Center Data Analytics Engineer

• Own data products end to end from source data through dashboards, metrics, or decision-making workflows
• Design, build, test, deploy, and maintain complete data product paths
• Partner with Marketing, Product, Finance, and Engineering to turn ambiguous questions into reliable data products
• Build testing, documentation, monitoring, and data quality controls
• Troubleshoot issues across pipelines, transformations, models, metrics, and reports
• Improve data architecture, simplify workflows, and automate repetitive work using AI responsibly
• Build data pipelines, dbt models, semantic views or AI agents in Snowflake, and Power BI dashboards
• Collaborate across the Business Intelligence & Data Engineering team and the broader Aceable organization

Senior Analytics Engineer

• Own production pipelines end-to-end, including design, development, monitoring, alerting, and iterative improvement
• Scope and deliver analytical features by shaping raw data into analytical models using Kimball Dimensional modeling with dbt
• Drive cross-functional delivery by identifying blockers, aligning stakeholders, and moving projects forward
• Use LLMs, agents, and other AI-assisted workflows to accelerate analysis and development
• Translate retail data, including inventory, on-shelf availability, and task execution signals, into business outcomes
• Establish best practices for reproducibility, documentation, and code quality
• Design and prototype conversational AI agent or chatbot interfaces for querying retail data through natural language

Staff/Senior Analytics Engineer, Data Science & Analytics

• Own Eve's go-to-market data model and establish standards for the analytics engineering team
• Build pipeline, funnel, campaign, and revenue models from HubSpot, DealHub, Apollo, and Clay in the warehouse and semantic layer
• Design, deploy, and maintain trusted semantic models for pipeline coverage, funnel conversion, CAC, win rate, sales cycle time, ARR, and bookings
• Build on source-to-staging models and conformed dimensions
• Instrument models for alerting to detect failures and drift
• Maintain documentation for owned models, metrics, and definitions
• Build internal AI agents and data-grounded tools for GTM stakeholders
• Own the metrics certification framework and catalog
• Define modeling standards and semantic-layer patterns
• Certify governed metric definitions and arbitrate conflicting definitions across teams
• Establish analytical application development patterns in Omni and Hex
• Partner with Sales, Marketing, Customer Success, and RevOps stakeholders
• Mentor analytics engineers and set the technical bar
• Report to the Head of Data Engineering

Staff Analytics Engineer

• Design, build, and operate high-throughput batch and streaming data pipelines using Kafka, Flink, and ETL technologies
• Design and build a unified analytics engine for large-scale data processing using Apache Spark and related tools
• Develop and optimize analytical data models for time-series, financial metrics, and trading activity
• Implement and manage analytical databases such as ClickHouse, MongoDB, BigQuery, and Snowflake with cost-aware architecture
• Build idempotent data pipelines with robust backfill and reconciliation capabilities
• Create comprehensive monitoring for data quality, freshness, and pipeline reliability
• Design, build, and operate internal AI platforms serving multiple trading teams
• Build reusable AI tooling, including standardized RAG pipelines, prompt management, and self-service workflows
• Create and maintain agent systems using LangGraph, A2A, and MCP, focusing on controllability and auditability

Analytics Engineer jobs in California

Program Tooling & Analytics Developer