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Dbt Developer Jobs in California (NOW HIRING)

OSI Digital

DBT Developer

Irvine, CA · On-site

$20 - $65/hr

Title DBT Developer Location Irvine, CA 5 days onsite Employment Contractor- 6 months Experience 4+ years About: At OSI Digital Inc, we accelerate our client's digital transformation journey by ...

OSI Digital

DBT Developer

Irvine, CA · On-site

$20 - $65/hr

Title DBT Developer Location Irvine, CA 5 days onsite Employment Contractor- 6 months Experience 4+ years About: At OSI Digital Inc, we accelerate our client's digital transformation journey by ...

OSI Consulting

DBT Developer

Irvine, CA · On-site

The Senior dbt Developer will design, build, and maintain scalable dbt transformation models on Snowflake, ensuring the conversion of raw data into analytics-ready datasets for reporting and decision ...

Staffingine LLC

DBT Architect

San Diego, CA · On-site

... Engineering Testing BI Review and approve design and deliverables Ensure adherence to timelines and quality standards Migration Modernization Lead ETL assessment and DBT transformation Drive ...

BirdEye Inc

Senior Financial Data Engineer

Palo Alto, CA · On-site

$124K - $169K/yr

Implement dbt best practices: modular design, ref() usage, incremental models, exposures, and a ... Serve as the data engineering liaison between Finance, Revenue Ops, and the broader Data ...

Centstone

Data Engineer

Sunnyvale, CA · On-site

$75 - $85/hr

Data Engineer Location: Sunnyvale, California (Onsite) Contract: 6 -12+ Months Experience: 12 - 15 ... The ideal candidate will have strong expertise in Snowflake, SQL, ETL, DBT, Tableau, Python, and ...

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All JobsDbt Developer JobsDbt Developer Jobs in California

Dbt Developer information

See California salary details

$16

$52

$80

How much do dbt developer jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for dbt developer in California is $52.15, according to ZipRecruiter salary data. Most workers in this role earn between $39.86 and $63.80 per hour, depending on experience, location, and employer.

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 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 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 popular job titles related to Dbt Developer jobs in California?

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

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

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

What cities in California are hiring for Dbt Developer jobs?

Cities in California with the most Dbt Developer job openings:

Dbt Developer jobs near you
Infographic showing various Dbt Developer job openings in California as of August 2026, with employment types broken down into 79% Full Time, 5% Part Time, 2% Temporary, and 14% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $108,466 per year, or $52.1 per hour.

DBT Developer

OSI Digital

Irvine, CA • On-site

$20 - $65/hr

Contractor

Re-posted 13 days ago

Job description

TitleDBT DeveloperLocationIrvine, CA 5 days onsiteEmploymentContractor- 6 months Experience4+ years
About:
At OSI Digital Inc, we accelerate our client's digital transformation journey by delivering modern data solutions that help organizations unlock the full value of their data through scalable cloud platforms, intelligent analytics, and business-ready reporting solutions. With deep expertise across data engineering, business intelligence, cloud platforms, advanced analytics, and AI/ML, our teams bring both technical excellence and business understanding to every engagement.
Role Summary:
We are seeking a Senior dbt Developer with strong hands-on experience in dbt, Snowflake, and advanced SQL development. The primary focus of this role is to design, build, test, document, deploy, and maintain scalable dbt transformation models on Snowflake that convert raw and source-aligned data into trusted, analytics-ready datasets for reporting, dashboards, and business decision-making.
The ideal candidate will have 4-5 years of experience in data engineering, analytics engineering, BI engineering, or modern data transformation roles, with practical experience using dbt Core and/or dbt Cloud in a production or project-based environment. This role requires strong SQL skills, Snowflake knowledge, good communication skills, and the ability to translate business rules and reporting requirements into reliable dbt models, reusable transformation logic, and governed data marts.
Key Responsibilities:
  • Design, build, and maintain modular dbt models across staging, intermediate, and marts layers that transform raw data into trusted, analytics-ready datasets.
  • Develop and optimize dbt incremental models, snapshots, macros, seeds, sources, and reusable packages using dbt Core and/or dbt Cloud.
  • Write and tune complex SQL transformations in Snowflake using joins, CTEs, window functions, aggregations, conditional logic, and performance optimization techniques.
  • Optimize Snowflake workloads for query performance, clustering strategy, warehouse sizing, model materialization, processing time, and cost efficiency.
  • Implement robust data quality and testing frameworks using dbt generic tests, singular tests, custom tests, accepted values, relationships, not-null checks, uniqueness checks, and source freshness checks.
  • Maintain clear documentation, lineage, dependency mapping, model descriptions, column definitions, source definitions, assumptions, and business logic using dbt docs and exposures.
  • Manage dbt projects in Git with clean, modular, testable development practices, including branching, pull requests, code reviews, merge controls, and release promotion.
  • Support CI/CD pipelines for dbt projects using tools such as GitHub Actions, GitLab CI, dbt Cloud jobs, or similar deployment and automation frameworks.
  • Leverage Snowflake features such as Streams, Tasks, Dynamic Tables, Time Travel, cloning, secure views, and secure data sharing to build reliable ELT workflows.
  • Create reporting-ready data marts, curated datasets, dimensional models, fact tables, and reusable views that support Tableau dashboards and self-service analytics.
  • Partner with data engineers, analysts, BI developers, architects, and business stakeholders to translate business requirements into scalable transformation logic.
  • Troubleshoot data discrepancies, failed dbt runs, source changes, schema changes, model errors, test failures, and performance bottlenecks.
  • Participate in requirement gathering sessions, technical design discussions, sprint planning, backlog refinement, walkthroughs, and UAT support activities.

Required Qualifications:
  • Minimum 4+ years of experience in data engineering, analytics engineering, BI engineering, data warehousing, or data transformation roles.
  • Strong hands-on experience with dbt Core and/or dbt Cloud, including dbt models, macros, tests, snapshots, seeds, sources, packages, documentation, lineage, and project structure.
  • Strong experience using dbt with Snowflake to build scalable ELT transformation pipelines, curated data models, and analytics-ready datasets.
  • Strong SQL development skills with experience writing complex transformations, performing data validation, troubleshooting data issues, and analyzing large datasets.
  • Strong understanding of dbt best practices for modular, testable, well-documented projects.
  • Hands-on Snowflake experience, including databases, schemas, tables, views, warehouses, roles, access controls, query optimization, and performance considerations.
  • Strong understanding of data modeling concepts, including star schema, fact and dimension tables, slowly changing dimensions, staging layers, data marts, and semantic/reporting layers.
  • Experience with data reconciliation and business rule validation.
  • Ability to translate business requirements, source-to-target mappings, metric definitions, and reporting logic into technical specifications and dbt transformation models.
  • Good troubleshooting and analytical skills with the ability to identify root causes of data issues, failed transformations, and performance bottlenecks.
  • Bachelor's degree in Computer Science, Engineering, Information Systems, Data Analytics, Business Analytics, or a related technical field. Equivalent practical experience may also be considered.

Preferred / Plus Qualifications:
  • Experience with Tableau, including understanding dashboard requirements, published data sources, extracts, live connections, and reporting-ready data model design.
  • Experience supporting BI and reporting teams by creating curated datasets, reusable views, semantic layers, and governed data marts.
  • Experience with advanced dbt capabilities such as dbt Explorer, dbt Semantic Layer, dbt Mesh, exposures, metrics, and cross-project lineage is a plus.
  • Experience with orchestration and scheduling tools such as Airflow, Dagster, Prefect, Azure Data Factory, Snowflake Tasks, dbt Cloud jobs, or similar platforms.
  • Experience with CI/CD processes for dbt projects using GitHub Actions, GitLab CI, Azure DevOps, Jenkins, or similar automation tools.
  • Experience with Python for automation, data validation, testing, metadata extraction, or data engineering support.
  • Experience with ELT tools such as Fivetran, Airbyte, Matillion, Informatica, Talend, Alteryx, or similar platforms.
  • Familiarity with cloud ecosystems such as AWS, Azure, or Google Cloud Platform.
  • Experience with Snowflake performance optimization, warehouse sizing, clustering, query profiling, access control, monitoring, and cost optimization.
  • Familiarity with Agile delivery, sprint planning, backlog management, Jira/Azure DevOps, and iterative development practices.
  • Understanding of data governance, metadata management, lineage, access control, PII handling, and enterprise data standards.
  • Certifications such as dbt Certified Developer, Snowflake certification, Tableau certification, or related cloud/data certifications are a plus.

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