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Senior Data Analytics Engineer Jobs in California

Hyperbolic

Senior Data Analytics Engineer

San Francisco, CA · On-site

$124K - $169K/yr

They are seeking their first data analytics hire to establish and own the data foundation for their ... Hyperbolic is the open-access AI cloud made for AI developers, providing fast, affordable access to ...

AmaWaterways, LLC

Data Analytics Engineer

Calabasas, CA · On-site

$90K - $100K/yr

Partner with the Senior Data Engineer to make sure the source pipelines you depend on are designed ... AI-native analytics engineering * Use Claude Code as your primary working environment, including ...

Living Spaces

Senior Data Analytics Developer

La Mirada, CA · On-site

$109.57 - $146.10/hr

R45009## Position Summary The Senior Data Analytics Developer will play a crucial role in ensuring relevant, timely, and actionable business integrations for Living Spaces. They will take charge of ...

Parafin, Inc

Data Analytics Engineer

San Francisco, CA · On-site

$180K - $220K/yr

About the Position We are looking for a Data Analytics Engineer to build and scale the data models, pipelines, and analytics infrastructure that power decision-making across Parafin. You'll design ...

Peterson

Data & Analytics Engineer

San Leandro, CA · On-site

$129K - $155K/yr

Peterson Cat has a need for a Data & Analytics Engineer to work onsite at our San Leandro, CA location. WE ARE UNABLE TO PROVIDE SPONSORSHIP AT THIS TIME SUMMARY The Data & Analytics Engineer is ...

Heluna Health

Data/Analytics Engineer

Los Angeles, CA · On-site

$10K/mo

This role sits at the intersection of data engineering and advanced analytics, responsible for the end-to-end design, implementation, and management of a governed Medallion Architecture (Bronze ...

PetersonCat

Data & Analytics Engineer

San Leandro, CA

$129K - $155K/yr

Peterson Cat has a need for a Data & Analytics Engineer to work onsite at our San Leandro, CA location. WE ARE UNABLE TO PROVIDE SPONSORSHIP AT THIS TIME SUMMARY The Data & Analytics Engineer is ...

Living Spaces

Senior Data Analytics Developer

La Mirada, CA · On-site

$109K - $146K/yr

Position Summary The Senior Data Analytics Developer will play a crucial role in ensuring relevant, timely, and actionable business integrations for Living Spaces. They will take charge of designing ...

HCVT

Senior Data & Analytics Specialist

Irvine, CA · On-site

This role combines expertise in data engineering, business intelligence, advanced analytics, and ... As the Senior Data & Analytics Specialist, you will be responsible for, but not limited to, the ...

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All JobsData Analytics Engineer JobsSenior Data Analytics Engineer JobsSenior Data Analytics Engineer Jobs in California

Senior Data Analytics Engineer information

See California salary details

$79.9K

$124.7K

$172.7K

How much do senior data analytics engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for senior data analytics engineer in California is $124,674.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $142,100.00 per year, depending on experience, location, and employer.

What does a senior data analytics engineer do?

A Senior Data Analytics Engineer is responsible for designing, developing, and maintaining scalable data pipelines and analytical solutions. They work closely with data scientists, analysts, and business stakeholders to gather requirements and ensure data quality and availability. Their role often includes optimizing data workflows, implementing best practices in data management, and mentoring junior team members. Additionally, they help translate business needs into technical solutions to support data-driven decision making.

How does a senior data analytics engineer typically collaborate with cross-functional teams to deliver insights?

As a Senior Data Analytics Engineer, you will frequently work with stakeholders in product, marketing, and engineering to translate business needs into data solutions. This involves gathering requirements, designing and building data pipelines, and presenting actionable insights. Effective communication and regular meetings with team members ensure that data models and dashboards align with business objectives. You may also mentor junior analysts and engineers, fostering a collaborative and knowledge-sharing environment.

What are the key skills and qualifications needed to thrive as a senior data analytics engineer, and why are they important?

To thrive as a Senior Data Analytics Engineer, you need expertise in statistics, data modeling, and programming languages such as Python or SQL, typically backed by a degree in computer science, engineering, or a related field. Experience with data analytics tools (e.g., Tableau, Power BI), cloud platforms (e.g., AWS, Azure), and relevant certifications like Google Data Engineer are highly valued. Strong problem-solving, communication, and leadership skills help you translate complex data insights into actionable business strategies and mentor junior team members. These capabilities are crucial for delivering accurate data-driven solutions that drive organizational decision-making and innovation.

What is the difference between Senior Data Analytics Engineer vs Data Scientist?

AspectSenior Data Analytics EngineerData Scientist
CredentialsBachelor's/Master's in Data Science, Computer Science, or related fieldsBachelor's/Master's in Data Science, Statistics, or related fields
Work EnvironmentFocus on data pipelines, analytics tools, and reporting systemsFocus on model development, statistical analysis, and predictive modeling
Industry UsageUsed in analytics teams to build data infrastructure and insightsUsed in R&D, product development, and research teams for modeling

While both roles require strong analytical skills and similar educational backgrounds, Senior Data Analytics Engineers primarily focus on building and maintaining data infrastructure and delivering insights through analytics tools. Data Scientists, on the other hand, concentrate on developing predictive models and statistical analysis. The roles often collaborate but serve different functions within data-driven organizations.

What are the most commonly searched types of Data Analytics Engineer jobs in California?

The most popular types of Data Analytics Engineer jobs in California are:

What are popular job titles related to Senior Data Analytics Engineer jobs in California?

For Senior Data Analytics Engineer jobs in California, the most frequently searched job titles are:

What job categories do people searching Senior Data Analytics Engineer jobs in California look for?

The top searched job categories for Senior Data Analytics Engineer jobs in California are:

What cities in California are hiring for Senior Data Analytics Engineer jobs?

Cities in California with the most Senior Data Analytics Engineer job openings:

Senior Data Analytics Engineer jobs near you
Infographic showing various Senior Data Analytics Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $124,674 per year, or $59.9 per hour.

Senior Data / Analytics Engineer

AgreeYa Solutions

Sacramento, CA • On-site

$115K - $156K/yr

Other

Posted yesterday

New

Job description

Title- Senior Data / Analytics Engineer GenAI & BI

Location- Sacramento, CA (hybrid/ 3days onsite)

Type- long term Contract-

Job Description-

Mandatory Qualifications:

  • At least seven (7) years of experience in the Information Technology (IT) field with extensive experience in report writing, data analysis, or database querying.
  • At least five (5) years of experience in data engineering, data warehousing, or BI analytics.
  • At least two (2) years of experience with ETL/ELT pipelines, cloud data warehouses such as Snowflake, Amazon Redshift, Azure Synapse, and orchestration tools (Airflow, dbt, etc.).
  • At least two (2) years of experience in SQL (advanced joins, window functions, performance tuning), data modeling (star/snowflake schemas, semantic layers), and hands-on experience with at least one major BI tool such as Power BI, Tableau, Looker.
  • At least two (2) years of hands-on experience in containerization and orchestration (Docker, Kubernetes), CI/CD pipelines for ML and data workflows, monitoring and logging for ML and BI systems, cloud infrastructure automation (Terraform, Ansible).

Desirable Qualifications:

  • Holding technical certifications in the areas of:
  • AWS certifications
  • Snowflake certifications
  • BI certifications (Power BI, Tableau)
  • AI/ML or GenAI-related coursework or credentials
  • At least five (5) years of experience in front-end UX/UI design for analytics dashboards and highly interactive reporting.
  • At least four (4) years of experience in development with React for or building scalable, highly customized production-grade user interfaces.
  • At least two (2) years of experience in front-end development with Chainlit or Streamlit for AI/ML or GenAI solutions with complex state management & data handling (e.g., real-time updates; UI states for loading, retries, and partial responses).
  • Experience and understanding in latency handling and async UX patterns, explainable AI interfaces (confidence, sources, disclaimers), and prompt design basics.
  • Hands-on experience and proven ability to build chat interfaces (streaming responses, token handling), and AI-assisted workflows (autocomplete, summarization, recommendations).
  • At least three (3) years of experience working with AI/ML or GenAI technologies.
  • At least one (1) year of hands-on experience using OpenAI APIs or similar LLM platforms, building natural language to SQL/query systems, designing prompt strategies for business insights, and prompt engineering to guide system behaviour.
  • At least three (3) years of experience in semantic layer design, data modelling, and delivering enterprise semantic models across multiple teams for large organizations.
  • At least one (1) year of experience in developing semantic models supporting natural language querying and AI-driven analytics (i.e., GenBI); statistical analysis, predictive analytics, and optimization.
  • Have a bachelor s degree in computer science, computer engineering, or related fields from an accredited or government sanctioned college/university.

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