Data Analytics Engineer Jobs in California
Data Analytics Engineer jobs in California are among the most active in the country, concentrated in technology, financial services, entertainment, and healthcare, with openings at every level from entry-level associate to principal engineer. The largest hiring metros are San Francisco, Los Angeles, and San Diego, where companies like Google, Salesforce, and Kaiser Permanente maintain deep data engineering teams. The most in-demand specialties are cloud data pipeline development, dbt and SQL-based transformation work, and analytics platform engineering. Find a role that fits below and apply directly.
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Showing 5 of 175+ Data Analytics Engineer jobs
- Own the end-to-end solution from data exploration and feature engineering through model training, validation, deployment, and performance monitoring.
- Develop and evaluate statistical and machine learning models, with clear justification for methodology and model selection.
- Write production-quality Python and SQL against multi-million-row datasets, with attention to performance, accuracy, and reliability.
- Translate ambiguous business questions into structured analyses and deliver actionable recommendations to stakeholders.
- Communicate analytical findings clearly to internal stakeholders, translating technical results into insights that support business decisions.
- Collaborate with data engineers in designing, validating, and maintaining ETL processes and data pipelines to ensure integrity, quality, and observability.
- Stay on top of emerging technologies in analytics, ML/AI, and cloud computing (familiarity with Snowflake and AWS SageMaker is a strong plus).
- Bachelor’s or Master’s degree in a quantitative discipline – Data Science, Engineering, Statistics, Mathematics, Computer Science, Economics, etc.
- 1–3 years of experience in Data Science, Engineering or a closely related role.
- Proven proficiency in Python (pandas, NumPy, scikit-learn) and SQL, with experience in data transformation, wrangling, and analysis against multi-million-row datasets.
- Working knowledge of statistical modeling and machine learning fundamentals, including model selection trade-offs, data leakage, class imbalance, and validation methodology.
- Hands-on experience across a range of modeling approaches, which may include regression and generalized linear models, tree-based and ensemble methods, time series forecasting, clustering, or neural networks.
- Solid working knowledge of relational databases — comfortable writing performant queries, optimizing slow ones, and reasoning about schemas, joins, and query plans at production scale.
- Demonstrated ability to work independently and manage competing priorities with limited supervision.
- Excellent communication skills with the ability to convey complex findings to both technical and non-technical audiences. A proactive, curious, and detail-oriented mindset with strong problem-solving abilities.
- Hands-on experience with business intelligence and visualization tools (Sigma, Tableau, Looker, or Power BI).
- Experience designing, validating, and maintaining ETL processes and data pipelines.
- Company sponsored Health, Dental, and Vision insurance
- 401K, traditional, and Roth with a company match
- Tuition Assistance or Tuition Reimbursement
- Unlimited Paid Time off
- Monthly Gym Reimbursement
- Paid time off to volunteer
- Paid Family Leave
- Complimentary office lunches
- Opportunity to grow
- Opportunity to work with a great team committed to making a difference.
- Salary Range: $100K to 120K (Based on experience) plus Bonus
- Own the end-to-end solution from data exploration and feature engineering through model training, validation, deployment, and performance monitoring.
- Develop and evaluate statistical and machine learning models, with clear justification for methodology and model selection.
- Write production-quality Python and SQL against multi-million-row datasets, with attention to performance, accuracy, and reliability.
- Translate ambiguous business questions into structured analyses and deliver actionable recommendations to stakeholders.
- Communicate analytical findings clearly to internal stakeholders, translating technical results into insights that support business decisions.
- Collaborate with data engineers in designing, validating, and maintaining ETL processes and data pipelines to ensure integrity, quality, and observability.
- Stay on top of emerging technologies in analytics, ML/AI, and cloud computing (familiarity with Snowflake and AWS SageMaker is a strong plus).
- Bachelor’s or Master’s degree in a quantitative discipline – Data Science, Engineering, Statistics, Mathematics, Computer Science, Economics, etc.
- 1–3 years of experience in Data Science, Engineering or a closely related role.
- Proven proficiency in Python (pandas, NumPy, scikit-learn) and SQL, with experience in data transformation, wrangling, and analysis against multi-million-row datasets.
- Working knowledge of statistical modeling and machine learning fundamentals, including model selection trade-offs, data leakage, class imbalance, and validation methodology.
- Hands-on experience across a range of modeling approaches, which may include regression and generalized linear models, tree-based and ensemble methods, time series forecasting, clustering, or neural networks.
- Solid working knowledge of relational databases — comfortable writing performant queries, optimizing slow ones, and reasoning about schemas, joins, and query plans at production scale.
- Demonstrated ability to work independently and manage competing priorities with limited supervision.
- Excellent communication skills with the ability to convey complex findings to both technical and non-technical audiences. A proactive, curious, and detail-oriented mindset with strong problem-solving abilities.
- Hands-on experience with business intelligence and visualization tools (Sigma, Tableau, Looker, or Power BI).
- Experience designing, validating, and maintaining ETL processes and data pipelines.
- Company sponsored Health, Dental, and Vision insurance
- 401K, traditional, and Roth with a company match
- Tuition Assistance or Tuition Reimbursement
- Unlimited Paid Time off
- Monthly Gym Reimbursement
- Paid time off to volunteer
- Paid Family Leave
- Complimentary office lunches
- Opportunity to grow
- Opportunity to work with a great team committed to making a difference.
- Salary Range: $100K to 120K (Based on experience) plus Bonus
See All 175+ Data Analytics Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find Data Analytics Engineer JobsData Analytics Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
Data Analytics Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Biotechnology & Pharmaceuticals
- Manufacturing
- Retail
- Education
What California Employers Look For
The qualifications that appear most often in data analytics engineer jobs across California.
- Bachelor's degree in computer science, statistics, mathematics, or a closely related field
- Proficiency in SQL and at least one scripting language such as Python or Scala
- Hands-on experience with cloud data platforms including BigQuery, Snowflake, or Databricks
- Familiarity with data modeling frameworks and transformation tools such as dbt
- Experience building or maintaining ETL and ELT pipelines in a production environment
- Strong communication skills for presenting data findings to non-technical California business stakeholders
Data Analytics Engineer Jobs in California: Frequently Asked Questions
How do you become a data analytics engineer in California?
California does not require a state-issued license or registration to work as a data analytics engineer. The standard path is a bachelor's degree in computer science, data science, mathematics, or a related field, followed by hands-on experience with SQL, Python, and cloud data platforms. Earning vendor certifications from Google Cloud, Snowflake, or dbt Labs strengthens a candidacy considerably in California's competitive technology market.
How much do data analytics engineers make in California?
Data analytics engineers in California earn a median of about $141,590 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $77,480 for the lowest 10% to over $224,920 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data analytics engineers in California?
Employers hiring data analytics engineers in California right now include Meta, Apple, and Intuit, based on current listings on Migrate Mate as of September 2026. California's concentration of technology headquarters, health systems, and financial services firms means consistent demand for this role across both established enterprises and growth-stage companies.
Which California cities have the most data analytics engineer jobs?
San Francisco, Los Angeles, and San Diego have the most data analytics engineer openings in California. The San Francisco Bay Area leads because of its density of technology headquarters and venture-backed companies, while Los Angeles reflects demand from entertainment, media, and e-commerce, and San Diego's concentration of biotech and defense firms drives openings there.
Are there remote data analytics engineer jobs in California?
Yes, and more than most fields. About 59% of data analytics engineer openings tied to California are remote or hybrid as of September 2026, reflecting that the work is largely desk-based and deliverable-driven. Pipeline development, data modeling, and analytics tooling work are the most consistently remote, while roles requiring close collaboration with embedded product or engineering teams tend to remain hybrid.
How can I get hired as a data analytics engineer in California with little or no experience?
The most realistic entry path is an associate or junior data engineer role at a mid-size California technology or healthcare company, where scope is more defined and mentorship more accessible. Large California employers such as Kaiser Permanente, Wells Fargo, and Apple run analyst and data associate programs that feed into engineering tracks. Building a public portfolio of dbt models, pipeline scripts, or Snowflake projects and earning a Google Cloud or Snowflake certification gives candidates a concrete edge over applicants without experience.
Where can I find and apply to data analytics engineer jobs in California?
You can find and apply to data analytics engineer jobs in California on Migrate Mate, which lists current California openings. Find roles that match your experience and location, then apply directly to the ones that fit.
See All 175+ Data Analytics Engineer Jobs in California
Find roles in California that match your experience and apply in just a few clicks.
Find Data Analytics Engineer Jobs