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Dbt Analytics Jobs in California (NOW HIRING)

AmaWaterways, LLC

Data Analytics Engineer

Calabasas, CA · On-site

$90K - $100K/yr

Governed semantic models in dbt for our top business KPIs: bookings, occupancy, revenue ... Cortex Analyst semantic YAML for natural-language data exploration by our internal users. * Data ...

Everpure

Senior Analytics Engineer, GTM

Santa Clara, CA · On-site

$122K - $168K/yr

We are midway through a strategic migration to dbt as our transformation standard. Beyond that, our ... As a Senior Analytics Engineer, you will help drive that journey end-to-end. This role is grounded ...

Prosum Inc.

Senior BI / Analytics Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

The ideal candidate brings deep expertise in dbt, Snowflake, Power BI, and modern ingestion platforms, with a strong foundation in data modeling, analytics engineering, and business intelligence best ...

Nutanix

Sr. Manager, Analytics Engineering

San Jose, CA · On-site

Build scalable analytical models and transformations using SQL, dbt, Python, Spark, or similar technologies. * Establish strong engineering practices for architecture reviews, testing, documentation ...

Nutanix

Sr. Manager, Analytics Engineering

San Jose, CA · On-site

Build scalable analytical models and transformations using SQL, dbt, Python, Spark, or similar technologies. * Establish strong engineering practices for architecture reviews, testing, documentation ...

Snowflake

Staff Analyst, GTM Analytics

Menlo Park, CA · On-site

$163K - $214K/yr

Maintain deep fluency in the data models, metrics, and pipelines (SQL, dbt, Snowflake) that power GTM reporting. Partner closely with Analytics Engineering and Data Engineering teams to ensure ...

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All JobsDbt Analytics JobsDbt Analytics Jobs in California

Dbt Analytics information

See California salary details

$37K

$63.1K

$90.8K

How much do dbt analytics jobs pay per year?

As of Aug 21, 2026, the average yearly pay for dbt analytics in California is $63,067.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,300.00 and $70,100.00 per year, depending on experience, location, and employer.

What is a dbt analytics?

A dbt Analytics job typically refers to a role focused on using dbt (data build tool) to transform, test, and document data within a data warehouse. Professionals in this field design and manage data models, write SQL-based transformations, and ensure data quality for analytics purposes. They collaborate with data engineers and analysts to build efficient, maintainable workflows that support business intelligence and data-driven decision-making. dbt Analytics jobs require strong SQL skills, familiarity with modern data stack tools, and an understanding of data modeling best practices.

What are the key skills and qualifications needed to thrive as a dbt analytics professional?

To thrive as a DBT Analytics professional, you need strong SQL skills, a solid understanding of data modeling, and experience with analytics engineering, typically backed by a degree in a quantitative field. Familiarity with the DBT (Data Build Tool) platform, cloud data warehouses like Snowflake or BigQuery, and version control systems such as Git is essential. Attention to detail, problem-solving abilities, and effective communication help you collaborate with stakeholders and ensure data reliability. These skills and tools are crucial for transforming raw data into actionable insights and maintaining robust, scalable analytics infrastructure.

How does a dbt analytics professional typically collaborate with data engineers and analysts within a team?

Dbt Analytics professionals play a key role in bridging the work of data engineers and data analysts. They transform raw data into clean, well-documented, and analysis-ready datasets using dbt (data build tool), ensuring consistency and reliability. Collaboration often involves working closely with data engineers to understand data sources and pipelines, while also partnering with analysts to tailor data models to business needs. Effective communication and regular feedback loops are crucial, as dbt professionals often serve as the link between technical data infrastructure and business-facing analysis.

What is the difference between Dbt Analytics vs Data Analyst?

AspectDbt AnalyticsData Analyst
Required CredentialsSQL, data modeling, analytics certificationsStatistics, Excel, SQL, sometimes certifications
Work EnvironmentData teams, analytics platforms, cloud environmentsBusiness units, reporting tools, spreadsheets
Industry UsageData transformation, modeling, analytics pipelinesData interpretation, reporting, insights

While Dbt Analytics focuses on transforming and modeling data within analytics workflows, Data Analysts primarily interpret data and generate reports. Both roles require SQL skills and work closely with data teams, but Dbt Analytics emphasizes data transformation using tools like dbt, whereas Data Analysts focus on analyzing and communicating insights.

Is dbt in demand?

Dbt analytics engineers are increasingly in demand as organizations adopt modern data transformation tools to improve data workflows. Skills in SQL, data modeling, and familiarity with cloud platforms enhance job prospects in this field, which is growing alongside the broader data analytics industry.

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

The most popular types of Dbt Analytics jobs in California are:

What are popular job titles related to Dbt Analytics jobs in California?

For Dbt Analytics jobs in California, the most frequently searched job titles are:

What job categories do people searching Dbt Analytics jobs in California look for?

The top searched job categories for Dbt Analytics jobs in California are:

What cities in California are hiring for Dbt Analytics jobs?

Cities in California with the most Dbt Analytics job openings:

Dbt Analytics jobs near you
Infographic showing various Dbt Analytics job openings in California as of August 2026, with employment types broken down into 1% Internship, 95% Full Time, 2% Part Time, and 2% Contract. Highlights an 77% Physical, 8% Hybrid, and 15% Remote job distribution, with an average salary of $63,067 per year, or $30.3 per hour.

Lead Data Engineer

DTEL Engineering & Consultants Inc

Irvine, CA • On-site

$122K - $147K/yr

Other

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Lead Data Engineer - MSS

Must Have Technical/Functional Skills

Data Bricks , EBT ,Airflow , Asset Management exp

Roles & Responsibilities

Lead Data Engineer MSS

Experience

8 15 Years

________________________________________

Role Overview

We are looking for a highly skilled Lead Data Engineer with strong hands-on experience in Databricks, dbt, and Python, and a proven track record of leading and executing data platform migration and modernization programs. The ideal candidate will have experience migrating legacy data warehouses, ETL platforms, and cloud/on-prem data ecosystems to a modern Databricks Lakehouse architecture using dbt-based transformation frameworks. This is a hands-on leadership role requiring deep technical expertise, solution design capabilities, and the ability to mentor engineering teams while driving enterprise-scale data modernization initiatives.

Key Responsibilities

Data Engineering & Development

  • Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, and Python.
  • Develop and optimize ELT/ETL processes for large-scale data ingestion and transformation.
  • Implement robust data quality, monitoring, and reconciliation frameworks.
  • Build reusable data engineering components and frameworks.

Data Platform Migration & Modernization

  • Lead migration of legacy data platforms, data warehouses, and ETL ecosystems to Databricks Lakehouse.
  • Transform existing ETL workloads to modern ELT patterns using dbt.
  • Analyze source environments and define migration approaches, roadmap, and execution strategy.
  • Drive code conversion, performance optimization, and workload modernization efforts.

Databricks Engineering

Develop solutions leveraging:

  • Databricks Lakehouse Platform
  • Delta Lake
  • Unity Catalog
  • Databricks Workflows
  • Structured Streaming
  • Medallion Architecture (Bronze, Silver, Gold)

Optimize Spark jobs and Databricks workloads for performance and cost efficiency.

dbt Development

  • Build and maintain dbt models, macros, tests, and documentation.
  • Implement incremental processing and reusable transformation frameworks.
  • Establish data lineage, testing, and CI/CD best practices.
  • Work closely with business and analytics teams to build trusted datasets.

Leadership & Collaboration

  • Lead a team of data engineers and developers.
  • Perform code reviews and enforce engineering standards.
  • Collaborate with archit ects, product owners, business analysts, and stakeholders.
  • Mentor junior engineers and drive adoption of best practices.

Apply