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Dbt Analytics Jobs in California (NOW HIRING)

About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared ... Together, we support thousands of organizations as they build a trusted foundation for analytics ...

About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared ... Together, we support thousands of organizations as they build a trusted foundation for analytics ...

Lead Data Engineer

Irvine, CA · On-site

$110K - $144K/yr

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 ...

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 ...

Senior BI / Analytics Engineer

Culver City, CA · On-site

$114K - $156K/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 ...

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 ...

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

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Showing results 1-20

Dbt Analytics information

See California salary details

$37K

$63.1K

$90.8K

How much do dbt analytics jobs pay per year?

As of Aug 31, 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 cities in California are hiring for Dbt Analytics jobs?

Cities in California with the most Dbt Analytics job openings:

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.

Staff Product Manager - dbt v2

Oakland, CA • Remote

Fivetran
Software Development • 1 - 5K employees

Full-time

Posted 5 days ago


Job description

About Us
Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data.
Together, we're delivering the data infrastructure layer that helps organizations move, transform, and trust their data - from the moment data moves, through every transformation, to the context teams and AI systems rely on.
Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions.
As we bring our teams and technology together, we're building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It's an exciting time to join us: we're creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact.
During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

About the role

We're hiring a Product Manager to lead the dbt v2 roadmap - the future of dbt Labs' intellectual property and a critical driver of product-led growth. You will own net-new functionality in Fusion that identifies and monetizes local deployments of dbt, shipping net new features, many of which also land in dbt Core, as well as proprietary ELv2 plugins that integrate seamlessly with the dbt platform.

This role is co-located with our dbt v2 engineering team in the US to accelerate execution, strengthen prioritization, and ensure tight alignment across product, engineering, and platform teams. You'll bridge open source product strategy with technical delivery and business impact, translating strategic investments into shipped features that drive the Fusion PLG motion.

In this role, you will

  • Own and deliver the dbt v2 roadmap, shipping net new functionality to dbt v2 like SQL comprehension, compute, governance, and SAO
  • Define requirements for Fusion features that integrate seamlessly with the dbt platform and unlock enterprise value
  • Keep the Fusion engineering team aligned, unblocked, and executing on a predictable cadence
  • Contribute hands-on to the dbt Core / Fusion codebases, including code reviews, documentation, and small feature implementations
  • Collaborate with OSS strategy leads, platform PM peers, and cross-functional stakeholders to deliver a unified roadmap

What success looks like

  • Shipping net-new features on a predictable quarterly cadence
  • Measurable contribution to Fusion PLG growth metrics, including identification and monetization of local dbt deployments
  • Hands-on contributions to dbt Core and Fusion code bases, including merged PRs and meaningful improvements to the open source codebase
  • Strong execution and alignment across the Fusion engineering team

You're a good fit if you have

  • 5+ years of product management experience in technical domains such as developer tooling, data platforms, or open source software
  • Strong grasp of system architectures, particularly for local deployments and how they scale to enterprise use cases
  • Understanding of how open source investments drive PLG growth and product strategy
  • Ability to bridge technical delivery with business impact, translating features into revenue and growth metrics
  • Experience working with engineering teams to define, prioritize, and ship complex technical features
  • Strong communication skills with empathy for open source contributors and enterprise users alike

Nice to have

  • Hands-on experience with dbt or similar transformation frameworks
  • Background in plugin architectures, extensibility systems, or platform ecosystems
  • Understanding of PLG motions and freemium-to-paid conversion strategies
  • Experience with SQL engines, query optimization, or compute systems
  • Prior experience as an engineer whose worked with modern development frameworks (examples: React, Typescript, Python, etc.)

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