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Analytical Engineer Jobs in California (NOW HIRING)

Plaid

Senior Analytics Engineer

San Francisco, CA · On-site

$123K - $169K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

The Analytics Engineering team owns the full-stack analytics foundation for Plaid's GTM, CGX, NEA ... questions into analytical answers * Enable self-serve analytics through AI tools and well ...

Plaid Inc

Senior Analytics Engineer

San Francisco, CA · On-site

$157K - $214K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

The Analytics Engineering team owns the full-stack analytics foundation for Plaid's GTM, CGX, NEA ... questions into analytical answers * Enable self-serve analytics through AI tools and well ...

Zipline

Senior Analytics Engineer

South San Francisco, CA · On-site

$125K - $172K/yr

  • Medical

  • Dental

  • Vision

  • PTO

As a Senior Analytics Engineer, you are the owner of analytics infrastructure and datasets that directly inform operational decisions across the company, ensuring planes launch on time, inventory is ...

DoorDash

Analytics Engineer

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

About the Team The Analytics Engineering team at DoorDash is embedded within the Analytics and Data Engineering Orgs, and is responsible for building internal data products that scale decision-making ...

G3

Analytics Engineer

Modesto, CA · On-site

Analytics Engineer Posting Start Date: 7/9/26 Summary The Analytics Engineer plays a key role on ... analytical and technical skills. Skilled in applying multiple technical solutions to business ...

Zipline

Senior Analytics Engineer

San Francisco, CA · On-site

$123K - $169K/yr

As a Senior Analytics Engineer, you are the owner of analytics infrastructure and datasets that directly inform operational decisions across the company, ensuring planes launch on time, inventory is ...

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Showing results 21-40

All JobsAnalytical Engineer JobsAnalytical Engineer Jobs in California

Analytical Engineer information

See California salary details

$38.5K

$100.4K

$135.7K

How much do analytical engineer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for analytical engineer in California is $100,420.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,900.00 and $115,000.00 per year, depending on experience, location, and employer.

What is the difference between Analytical Engineer vs Data Scientist?

AspectAnalytical EngineerData Scientist
Required CredentialsBachelor's or Master's in Engineering, Data Analytics, or related fieldsBachelor's or Master's in Computer Science, Statistics, or related fields
Work EnvironmentEngineering teams, product development, manufacturingData analysis, modeling, research teams
Industry UsageManufacturing, tech, automotive, aerospaceTech, finance, healthcare, e-commerce
Common Search IntentTechnical analysis, process optimizationData modeling, predictive analytics

Analytical Engineers focus on applying engineering principles to analyze and optimize systems and processes, often working closely with product and manufacturing teams. Data Scientists primarily analyze data to extract insights, build models, and support decision-making. While both roles require analytical skills, their focus areas and typical environments differ, making this comparison useful for those exploring career options or job opportunities.

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

To thrive as an Analytical Engineer, you need a solid background in engineering principles, data analysis, and problem-solving, typically supported by a relevant engineering degree. Proficiency with analytical software such as MATLAB, Python, or finite element analysis (FEA) tools, along with familiarity with industry-specific systems, is essential. Strong communication, critical thinking, and teamwork skills help Analytical Engineers translate complex data into actionable insights and collaborate effectively. These abilities are crucial for developing reliable solutions, optimizing processes, and supporting informed decision-making within technical teams.

How does an analytical engineer typically collaborate with cross-functional teams during a project?

Analytical Engineers frequently work alongside product managers, designers, and software developers to translate business goals into quantifiable metrics and actionable insights. They participate in planning meetings to define project requirements, develop data models, and present analytical findings that inform decision-making. Effective communication and the ability to explain complex data in accessible terms are essential, as Analytical Engineers often bridge the gap between technical and non-technical team members. This collaborative environment fosters a shared understanding of project objectives and helps ensure that solutions align with both technical feasibility and business needs.

Do analytics engineers make good money?

Analytics engineers typically earn competitive salaries that vary based on experience, location, and industry. They often have skills in SQL, data modeling, and tools like dbt or Looker, which can contribute to higher compensation. Overall, the role is considered well-paying within the data and analytics field.

Are analytical engineers in demand?

Analytical engineers are in high demand across industries such as manufacturing, technology, and energy due to their expertise in data analysis, process optimization, and system modeling. Employers seek professionals skilled in tools like MATLAB, Python, and data visualization, often requiring a strong background in engineering principles and certifications. The role offers growth opportunities as companies increasingly rely on data-driven decision-making.

What is an analytical engineer?

Analytical Engineers are professionals who use advanced mathematical, statistical, and computational techniques to analyze data and solve complex engineering problems. They often work on developing models, simulations, and analytical tools to improve product design, optimize processes, or predict system behaviors. Their role bridges the gap between data analysis and traditional engineering, enabling more data-driven decision making within engineering projects.

What are popular job titles related to Analytical Engineer jobs in California?

For Analytical Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Analytical Engineer jobs in California look for?

The top searched job categories for Analytical Engineer jobs in California are:

Analytical Engineer jobs near you
Infographic showing various Analytical Engineer job openings in California as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 7% Part Time, 2% Temporary, and 3% Contract. Highlights an 84% Physical, 6% Hybrid, and 10% Remote job distribution, with an average salary of $100,420 per year, or $48.3 per hour.

Senior Analytics Engineer

Plaid

San Francisco, CA • On-site

$123K - $169K/yr

Other

Medical, Dental, Vision, Retirement

Re-posted 16 days ago

Job description

We believe that the way people interact with their finances will drastically improve in the next few years. We're dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid's network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam.
The Analytics Engineering team owns the full-stack analytics foundation for Plaid's GTM, CGX, NEA and Marketing organizations. We build and maintain the core semantic layer data models (dbt on Databricks), activation layer, and BI surfaces that these teams rely on - and we partner with stakeholders to turn those models into decisions, forecasts, analytics and experiments.
As a Senior Analytics Engineer, you'll also act as an applied data science partner. In addition to core analytics engineering, you'll work on predictive modeling, experimentation, lifetime value (LTV), and attribution alongside the broader team.
As a Senior Analytics Engineer on the Marketing pod, you will be the technical owner of Plaid's Marketing data stack. You will build the dbt models, predictive frameworks, and self-serve data products that Marketing leadership uses to plan spend, measure performance, and drive growth.
You'll partner directly with PMM, Growth Marketing, and Marketing leadership to deliver core data models, frameworks, and tools - including LTV, lead scoring, and experimentation tooling - with a north star that aims for prescriptive and production-grade analytics. You'll also help build the AI-powered experiences that let Marketing partners self-serve from our metric layer
Responsibilities
  • Own the dbt models and data marts that power Marketing analytics, activation, and reporting.
  • Build, validate, and productionize predictive models (lead scoring, LTV, channel attribution, propensity) in partnership with Marketing and GTM stakeholders
  • Partner with Marketing leadership on measurement frameworks, experiment design, and spend optimization - translating business questions into analytical answers
  • Enable self-serve analytics through AI tools and well-documented semantic models
  • Collaborate with ML, Data Engineering, and Ops teams to deliver best-in-class data infrastructure to Marketing

Qualifications
  • Bachelor's degree in a quantitative field (CS, Statistics, Economics, Engineering, or equivalent experience)
  • 5+ years of proven experience in analytics engineering, data science, or a closely adjacent function
  • Advanced SQL and production-grade data modeling experience - dbt strongly preferred
  • Python proficiency for modeling and analysis work
  • Hands-on experience with a modern cloud warehouse (Databricks, Snowflake, BigQuery, or Redshift)
  • Demonstrated experience shipping predictive models or applied ML in a business context
  • Prior experience in Marketing Analytics, Growth, or GTM analytics at a SaaS or usage-based technology company
  • Strong stakeholder communication and the ability to autonomously drive projects end-to-end

Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn't fully match the job description. We are always looking for team members that will bring something unique to Plaid!
Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at
Please review our Candidate Privacy Notice here.
Additional compensation in the form(s) of equity and/or commission are dependent on the position offered. Plaid provides a comprehensive benefit plan, including medical, dental, vision, and 401(k). Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

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