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

Broccoli AI

Data Analytics Engineer

San Francisco, CA · On-site

$134K - $162K/yr

Ad-hoc analyses, segment investigations, partner questions. * Work closely with engineering. Understand how our systems store and produce data, including schemas, events, and architecture, and give ...

Deloitte

GCP Cloud Analytics Engineer

San Jose, CA · On-site

$65.25 - $87.25/hr

GCP Cloud Analytics Data-driven organizations need modern cloud analytics solutions that turn information into insight and action. As a Sr Consultant, GCP Cloud Analytics, you will help clients ...

Deloitte

GCP Cloud Analytics Engineer

San Francisco, CA · On-site

$65.75 - $87.75/hr

GCP Cloud Analytics Data-driven organizations need modern cloud analytics solutions that turn information into insight and action. As a Sr Consultant, GCP Cloud Analytics, you will help clients ...

Kikoff

Senior Data Engineer

San Francisco, CA · On-site

$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 ...

Nutanix

Sr. Manager, Analytics Engineering

San Jose, CA · On-site

If so, joining our team as a Senior Manager, Analytics Engineering at Nutanix will allow you to make a meaningful impact by influencing data-driven decision-making across the organization and driving ...

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All JobsAnalytics Engineer JobsAnalytics Engineer Jobs in San Ramon, CA

Analytics Engineer information

What do analytics engineers do?

Analytics engineers design, build, and maintain data pipelines and infrastructure to enable data analysis and reporting. They work with tools like SQL, Python, and data warehouses to ensure data is accurate, accessible, and well-structured for analysts and data scientists. Their role often involves collaborating with teams to optimize data workflows and ensure data quality.

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 are popular job titles related to Analytics Engineer jobs in San Ramon, CA? For Analytics Engineer jobs in San Ramon, CA, the most frequently searched job titles 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 93% Full Time, and 7% Contract. Highlights an 88% In-person, and 12% Remote job distribution.

Data Analytics Engineer

Broccoli AI

San Francisco, CA • On-site

$134K - $162K/yr

Full-time

Posted 8 days ago

Job description

About Broccoli
At Broccoli, we're building AI teammates for the people who build and maintain our world.
We partner with plumbing, HVAC, and electrical contractors, the hardworking businesses that keep homes and communities running, and replace fragmented software and repetitive manual work with AI that actually gets the job done.
Our AI teammates answer phones, book appointments, follow up with customers, recover missed revenue, and help contractors deliver exceptional customer experiences, all while integrating seamlessly with platforms like ServiceTitan.
Before we wrote a single line of code, we visited more than 140 contractors to understand how these businesses truly operate. That firsthand experience shaped everything we've built.
Today:
  • Hundreds of contractors rely on Broccoli every day.
  • We've grown to $15M+ ARR in under two years.
  • We're trusted by everyone from independent contractors to some of the largest private equity backed operators in the home services industry.
  • We're backed by Khosla Ventures and Y Combinator.

We're still just getting started.
About the role
Our data is rich and comes from many sources. Every customer dashboard, every business review, every metric the company runs on draws from it - and we haven't yet built the unified data layer that makes all of that fast, consistent, and ready to scale.
You'll build that layer and own it. You'll model our data into clean, documented tables and build the source-of-truth library and own the data definitions the whole team runs on. You'll work hand in hand with the Strategy & Ops team - and essentially every tool we build, especially the external-facing dashboards and analytics our customers see, will be built on your work.
You're the team's first dedicated data hire: you own the architecture, the tooling choices, and the trust in every number. What you build powers customer-facing dashboards, cross-customer benchmarks, and eventually the business intelligence we ship inside the product.
What you'll do
  • Build and run the pipelines. Reliable ingestion from all our sources into ClickHouse - you choose the tooling and own the flow.
  • Model the data. Turn raw feeds into clean, documented tables - including entity resolution, so a customer is the same customer across billing, support, and call data.
  • Build the source-of-truth library. Canonical views and metric definitions that every dashboard and analysis reads from.
  • Make the data Human & AI-ready. Structure our models, definitions, and documentation so both people and AI agents can query them and get the right answer - then build the internal tools that let anyone at Broccoli ask a data question and trust the response.
  • Keep it trustworthy. Freshness checks, quality tests, and alerts - we find out a pipeline broke before a customer does.
  • Run deep dives when the team needs them. Ad-hoc analyses, segment investigations, partner questions.
  • Work closely with engineering. Understand how our systems store and produce data, including schemas, events, and architecture, and give input early on changes so the data that lands in the warehouse is usable, stable, and easy to model.
What we're looking for
  • 4-8+ years in data or analytics engineering - you've built and operated production pipelines end to end, and been the one paged when they broke.
  • Strong SQL and solid Python; hands-on with ETL tooling (Airbyte, Fivetran, Dagster, dbt, or hand-rolled) and orchestration.
  • Real experience with a columnar/OLAP warehouse - ClickHouse ideally; BigQuery, Snowflake, or Redshift transfer fine.
  • Data modeling as a craft: you've designed the tables other people query, and you care what the numbers mean, not just that the pipes run.
Nice to have
  • Self-directed: you've been the first or only data person somewhere, or built a data platform from scratch
  • ClickHouse specifically - materialized views, performance tuning on event-scale data.
  • Multi-source identity / entity resolution experience.
  • Exposure to customer-facing or multi-tenant analytics (strict customer-level data isolation).
  • B2B SaaS operational data - calls, bookings, jobs, billing - or CRM/field-service data like ServiceTitan.

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