ZipRecruiter

Log In

1

Analytics Engineer Jobs in San Ramon, CA (NOW HIRING)

Kikoff

Senior Data Engineer

San Francisco, CA

$124K - $169K/yr

We are looking for a Data Engineer or Analytics Engineer to join our Data team. You will collaborate with the data scientist and engineers to design, build, and scale high-leverage data models ...

Pilot.com

Senior Data Engineer

San Francisco, CA · On-site

$124K - $169K/yr

They are seeking a Senior Analytics Engineer to own and architect their data foundation, ensuring that it supports the company's AI-native services and enables teams to leverage data effectively.

JLL

Analytics Specialist Developer

San Francisco, CA · On-site

The Analytics Specialist Developer is an experienced delivery role within JLL's Analytics Centre of Excellence, responsible for building and owning complex analytics solutions (Tableau, Power BI ...

Kikoff

Senior Data Engineer

San Francisco, CA · On-site

$226K - $254K/yr

We are looking for a Data Engineer or Analytics Engineer to join our Data team. You will collaborate with the data scientist and engineers to design, build, and scale high-leverage data models ...

Samsung

Data Analytics Developer

San Jose, CA

Company Description We are seeking a developer to join the data analytics team with at least 5 years of software development experience. The candidate must have experience with distributed systems ...

Samsung

Data Analytics Developer

San Jose, CA · On-site

Company Description We are seeking a developer to join the data analytics team with at least 5 years of software development experience. The candidate must have experience with distributed systems ...

next page

Showing results 1-20

All JobsAnalytics Engineer JobsAnalytics Engineer Jobs in San Ramon, CA

Analytics Engineer information

What are the key skills and qualifications needed to thrive as an Analytics Engineer, and why are they important?

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

How does an Analytics Engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

What is an Analytics Engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.
What are the most commonly searched types of Analytics Engineer jobs in San Ramon, CA? The most popular types of Analytics Engineer jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Analytics Engineer jobs? Cities near San Ramon, CA with the most Analytics Engineer job openings:
Analytics Engineer jobs near you
Infographic showing various Analytics Engineer job openings in San Ramon, CA as of July 2026, with employment types broken down into 96% Full Time, and 4% Contract. Highlights an 79% In-person, and 21% Remote job distribution.
Member of Technical Staff (Analytics Engineer)

Member of Technical Staff (Analytics Engineer)

Perplexity

San Francisco, CA • On-site

Full-time

Re-posted 25 days ago

Job description

Job Summary:
Perplexity is an AI company focused on transforming how data science is conducted. They are seeking a Member of Technical Staff (Analytics Engineer) to build AI systems that enhance data workflows, create AI-readable infrastructures, and automate data processes to improve efficiency and effectiveness across the organization.
Responsibilities:
• Accelerate the AI-native data workflow - the team is already working this way. You'll take what's working and turn it into repeatable systems, scalable tools, and patterns that the data team and the entire company can adopt
• Build AI agents that do data science - not just answer SQL questions, but conduct end-to-end analyses: explore data, form hypotheses, run queries, interpret results, and generate actionable recommendations
• Make the warehouse AI-readable - build the semantic layer, context, and retrieval infrastructure that lets any AI system (internal or product) query Perplexity's data accurately and reliably
• Automate the data lifecycle - self-healing pipelines, automated dbt model generation and validation, data quality agents that detect, diagnose, and fix issues autonomously
• Ship AI-powered experiment analysis - agents that interpret A/B test results, flag statistical issues, and draft ship/no-ship recommendations for product teams
• Own the full lifecycle - from identifying the highest-leverage problem, to prototyping with LLMs, to iterating on accuracy and UX, to production deployment and monitoring
• Turn the data team into a product team - build internal data products that stakeholders across the company actually use daily, replacing ad-hoc requests with self-serve AI interfaces
Qualifications:
Required:
• 6-8+ years in data science, analytics engineering, or a related role - you've been in the data trenches
• Strong product sense - you've worked closely with product and business teams, you understand what drives user behavior, and you have good instincts for what to measure and what to build
• Deep SQL expertise - you think in SQL, you've built data models, you know your way around a warehouse
• Pipeline experience - you've built and maintained data pipelines, worked with dbt, dealt with data quality issues firsthand
• Enough software engineering chops to be dangerous - you can build and ship a working tool in Python, not just a notebook. You can wrangle APIs, deploy a service, write code that other people can maintain. You're not a SWE, but you're not afraid of production
• Genuinely excited about AI - you've been building with LLMs on your own time. You have opinions about which models are good at what. You've tried building agents, RAG systems, or AI-powered workflows. You follow the space obsessively because you think it's going to change everything - including how data teams work
• Builder mentality - you see a manual process and you can't help but automate it. You ship fast and iterate
• Autonomy - this is a new function. You'll define the roadmap as much as execute it
Preferred:
• Experience with dbt (building and maintaining production models)
• Snowflake administration and optimization
• You've built Slack bots, internal CLI tools, or developer productivity tools that people actually used
• Background in AI agent frameworks
• Experience with BI tools - you know what's worth automating because you've done the manual version
• A/B testing and experimentation - you've designed experiments and analyzed results
• Early-stage startup experience
Company:
Perplexity is an AI-powered platform that retrieves, analyzes information from the web to deliver structured answers with cited sources. Founded in 2022, the company is headquartered in San Francisco, USA, with a team of 201-500 employees. The company is currently Growth Stage.

Apply