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Dbt Developer Jobs in Anaheim, CA (NOW HIRING)

Northern Base

Lead Data Engineer

Irvine, CA · On-site

$110K - $144K/yr

Lead Data Engineer - MSS Irvine, CA Fulltime Lead Data Engineer - MSS Must Have Technical ... Transform existing ETL workloads to modern ELT patterns using dbt. * Analyze source environments ...

Banc of California

VP, Analytics Engineering

Santa Ana, CA · On-site

$58.17 - $97.12/hr

Guide reusable dbt models, macros, and semantic models, and lead dimensional data modeling ... Experience with Git, Azure DevOps or comparable tools, CI/CD, pull requests, and automated quality ...

Banc of California

VP, Analytics Engineering

Santa Ana, CA · On-site

$187K - $241K/yr

Guide reusable dbt models, macros, and semantic models, and lead dimensional data modeling ... Experience with Git, Azure DevOps or comparable tools, CI/CD, pull requests, and automated quality ...

New

Plug

Sr. Data Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

Engineering Location: Onsite-Santa Monica, CA Employment Type: Full-time, Salaried, Exempt Reports ... Own the dbt transformation layer - staging, intermediate, and mart models and MetricFlow ...

New

OSTechnical

Be Seen First

Data Engineer

Irvine, CA · On-site

$100K - $115K/yr

Data Engineer with a client at Irvine, CA Contract to hire. Position Summary The Engineer, Data ... Design and develop ETL/ELT pipelines using Snowflake, dbt, Matillion, and Python. * Integrate data ...

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All JobsDbt Developer JobsDbt Developer Jobs in Anaheim, CA

Dbt Developer information

See Anaheim, CA salary details

$17

$55

$85

How much do dbt developer jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for dbt developer in Anaheim, CA is $55.32, according to ZipRecruiter salary data. Most workers in this role earn between $42.26 and $67.69 per hour, depending on experience, location, and employer.

What is a dbt developer?

A Dbt Developer is a data professional who specializes in using dbt (data build tool) to transform raw data into clean, reliable datasets for analytics and business intelligence. They write modular SQL code to perform data transformations, manage data models, and ensure data quality within modern data warehouses. Dbt Developers collaborate closely with data engineers, analysts, and business users to create efficient, maintainable data workflows. Their work enables organizations to make informed decisions based on trustworthy and well-structured data.

How does a dbt developer typically collaborate with data engineers and analysts on a project?

DBT Developers frequently work alongside data engineers to ensure that data pipelines provide clean, reliable data to downstream users. They collaborate with analysts to understand data requirements, define business logic, and implement transformations that support analytics and reporting. Regular communication is essential for aligning on naming conventions, documenting models, and troubleshooting issues. This collaboration often takes place through code reviews, shared documentation, and agile ceremonies such as sprint planning or stand-ups.

What are the key skills and qualifications needed to thrive as a dbt developer, and why are they important?

To thrive as a DBT Developer, you need strong SQL expertise, data modeling skills, and experience with ETL processes, typically supported by a background in computer science or data engineering. Familiarity with DBT (Data Build Tool), version control systems like Git, and cloud data warehouses such as Snowflake or BigQuery is essential. Attention to detail, problem-solving abilities, and effective communication help you deliver scalable data solutions and collaborate with cross-functional teams. These skills are crucial for building reliable data pipelines, ensuring data quality, and enabling data-driven decision-making within organizations.

What is the difference between Dbt Developer vs Data Engineer?

AspectDbt DeveloperData Engineer
Primary FocusBuilding and maintaining data transformation pipelines using dbtDesigning, developing, and managing data infrastructure and pipelines
Skills & CertificationsSQL, dbt, data modeling, analytics skillsSQL, Python, ETL tools, cloud platforms, data architecture
Work EnvironmentAnalytics teams, data warehouses, BI projectsData platforms, cloud environments, big data systems

While both roles involve working with data, a Dbt Developer specializes in transforming data using dbt within analytics and BI projects, whereas a Data Engineer focuses on building and maintaining the broader data infrastructure and pipelines across various systems.

What job categories do people searching Dbt Developer jobs in Anaheim, CA look for?

The top searched job categories for Dbt Developer jobs in Anaheim, CA are:

What cities near Anaheim, CA are hiring for Dbt Developer jobs?

Cities near Anaheim, CA with the most Dbt Developer job openings:

Dbt Developer jobs near you
Infographic showing various Dbt Developer job openings in Anaheim, CA as of August 2026, with employment types broken down into 88% Full Time, 2% Part Time, and 10% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $115,060 per year, or $55.3 per hour.

Snowflake DBT Data Engineer C2C jobs in Irvine CA

Tech Mirrors

Irvine, CA • On-site

$140 - $170/hr

Other

Posted 2 days ago

New

Job description

Snowflake DBT Data Engineer


Location Irvine CA 5 Day onsite


Required technical skills for DBT Snowflake role


Develop DBT Projects Build maintain and manage the end-to-end DBT project ensuring modularity reusability and adherence to established data standards


Advanced SQL Jinja Write complex optimized SQL queries and leverage Jinja templating within DBT models for dynamic transformations and efficient code


Snowflake Data Cloud Architecture Virtual Warehouses Role Based Access Control Time Travel Zero Copy Clones Objects and SQL Scripting


Data Modeling Implementation Design and implement dimensional data models eg Star Schema in Snowflake to serve business intelligence reporting and data science needs


Materialization Strategy Configure and optimize DBT materialization strategies views tables incremental models Dynamic Tables to balance data freshness query performance and Snowflake compute costs


Automated Testing Embed comprehensive data quality and integrity tests ex schema checks referential integrity directly into DBT models using DBT tests and custom checks


Documentation Lineage Maintain high-quality DBT documentation and ensure complete data lineage is tracked and visible for all transformed models


Orchestration CICD Integrate the DBT project with orchestration tools eg Dagster and establish CICD pipelines eg BitBucket for reliable automated deployment of code from development to production environments

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