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Dbt Analytics Jobs (NOW HIRING)

OR · On-site

Define and execute a multi-year joint strategy that positions dbt and Fivetran as the default analytics engineering and transformation layer within Microsoft's Fabric and Azure data ecosystem

Solutions Architect, Commercial

Austin, TX · On-site

$62.50 - $82.25/hr

... analytics * Strong technical foundation, with a solid understanding of modern data warehousing architectures, the modern data stack, and proficiency in SQL * Prior experience with dbt is preferred ...

AI Search Analyst

New York, NY · On-site

$115K - $145K/yr

BigQuery, ClickHouse, Postgres, dbt * Analytics: dashboards, notebooks, experimentation, reporting workflows Benefits for full-time US employees: Wellbeing: Medical, dental, vision, and life ...

Data Engineering Lead

East Rutherford, NJ · On-site

$168K - $210K/yr

Data Modeling & Analytics Engineering: dbt, analytics-ready and semantic data modeling * Metadata, Lineage & Quality: OpenMetadata, OpenLineage, data quality testing, data observability * DevOps & ...

Data Architect

Piscataway, NJ · On-site

$106K - $155K/yr

Relevant certifications such as Certified Data Management Professional (CDMP) or cloud-specific data certifications (eg., Snowpro Advanced Architect, dbt Analytics Engineer, or GCP Professional Cloud ...

About the Role We're looking for a Director of Business Analytics Engineering to lead and grow the ... Own and evolve our dbt + Snowflake transformation layer, including modeling standards, testing ...

About the Role We're looking for a Director of Business Analytics Engineering to lead and grow the ... Own and evolve our dbt + Snowflake transformation layer, including modeling standards, testing ...

Data Modeling & Analytics Engineering • Design, build, and maintain analytics ready data models using dbt, following dimensional and semantic modeling best practices (e.g., star schemas, marts ...

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Dbt Analytics information

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$37.5K

$63.9K

$92K

How much do dbt analytics jobs pay per year?

As of Jul 4, 2026, the average yearly pay for dbt analytics in the United States is $63,903.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,000.00 and $71,000.00 per year, depending on experience, location, and employer.

What is a dbt Analytics job?

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, and why are they important?

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.

More about Dbt Analytics jobs
What cities are hiring for Dbt Analytics jobs? Cities with the most Dbt Analytics job openings:
What are the most commonly searched types of Dbt Analytics jobs? The most popular types of Dbt Analytics jobs are:
What states have the most Dbt Analytics jobs? States with the most job openings for Dbt Analytics jobs include:
Staff Product Manager- Developer Experience

Staff Product Manager- Developer Experience

dbt Labs

OR • Remote

Other

Medical, Retirement, PTO

Posted 24 days ago


Job description

About the Role

The way data practitioners write, debug, and ship dbt code is changing fast - and you'll be the person shaping what that experience looks like at the frontier of AI-assisted development.

As the Product Manager for Developer Experience, you will own the end-to-end developer workflow in dbt Cloud: the Studio IDE, Developer Agent (our AI coding assistant), the Cloud CLI, and the dbt VS Code Extension. Together, these surfaces are the primary daily touchpoint for tens of thousands of data practitioners worldwide - from seasoned analytics engineers writing complex SQL to newer practitioners who rely on AI to help them move faster and with more confidence.

This role sits at the intersection of developer tooling and leading-edge AI. You will work in close partnership with the Fusion team - the engine powering dbt's next-generation compilation, intelligence, and platform capabilities - to ensure that our developer surfaces fully leverage Fusion's capabilities and that developer needs are represented in the Fusion roadmap. The tight feedback loop between Developer Experience and Fusion is core to how dbt Cloud will evolve, and you'll be a key architect of that relationship.

This is a role for someone who has thought deeply about what makes IDEs and developer tools great, and who is excited to reimagine those workflows in an era where AI can lower the floor for new practitioners while raising the ceiling for experts.


In This Role, You Will
  • Own the developer experience roadmap across Studio IDE, Developer Agent, Cloud CLI, and the VS Code Extension - from near-term iteration to long-term vision.
  • Partner deeply with the Fusion team to align on capabilities, surface Fusion-powered intelligence (SQL comprehension, compute, context) through developer-facing UX, and co-define the boundary between platform and product.
  • Lead AI-native product development for Developer Agent - defining what a best-in-class AI coding assistant looks like for the full spectrum of dbt users, from expert analytics engineers to practitioners who are newer to code. This includes agentic workflows, context-aware suggestions, natural language interactions, and guided development experiences that meet users where they are.
  • Drive IDE and tooling strategy informed by a deep understanding of modern development environments - think about what VS Code, Cursor, and other leading IDEs get right, and translate those instincts to the dbt Cloud context.
  • Define and execute cross-functional collaboration with engineering, design, and GTM teams to ship high-quality developer experiences on a predictable cadence.
  • Build tight feedback loops with the dbt community and enterprise customers to continuously improve developer tools, with particular attention to power users and technical practitioners.
  • Conduct market and user research to understand the competitive landscape for developer tooling and AI-assisted development, and bring sharp external perspective into the roadmap.
  • Align developer experience investments to broader company goals, product-led growth metrics, and the Fusion platform strategy.

What Success Looks Like
  • Developer satisfaction and engagement metrics (activation, session depth, feature adoption) trending up across Studio, Canvas, CLI, and Developer Agent.
  • Developer Agent is a differentiated, well-regarded AI coding experience for data practitioners - not just a feature, but a product.
  • The Studio IDE and Canvas deliver a cohesive, fast, and intelligent development workflow powered by Fusion capabilities.
  • Strong, trust-based execution partnership with the Fusion team: shared roadmap visibility, clear API contracts, and coordinated shipping.
  • The Cloud CLI is a first-class product that developers actively choose, not a fallback.

You're a Good Fit If You Have
  • 5+ years of product management experience, with meaningful time spent on developer tools, IDEs, or technical platforms.
  • Direct experience managing IDE or developer environment products - you have an informed point of view on what makes development tools excellent and where modern IDEs fall short.
  • Demonstrated engagement with AI-powered development tools - you've used, studied, and formed strong opinions about AI coding assistants (Copilot, Cursor, Devin, etc.) and how they change the development experience.
  • A strong technical foundation that allows you to work fluently with engineering partners, reason about system architecture, and contribute meaningfully to technical decisions.
  • Experience conducting user research and translating developer feedback into prioritized, scoped product work.
  • Excellent written and verbal communication - you can write a crisp spec, give a compelling demo, and synthesize complex tradeoffs for diverse audiences.
  • Comfort working asynchronously as part of a distributed, remote team.

You'll Have an Edge If You Have
  • Hands-on experience with dbt or similar SQL-first transformation frameworks.
  • Prior experience building or shipping AI agent features (agentic UX, multi-step LLM workflows, context management).
  • Familiarity with LSP (Language Server Protocol), tree-sitter, or other IDE infrastructure primitives.
  • Experience with CLI tooling and developer workflow automation.
  • Background in open source software development or strong engagement with developer communities.
  • Knowledge of modern data warehouses (Snowflake, BigQuery, Databricks, Redshift, etc.) and the analytics engineering ecosystem.
Compensation & Benefits

Salary: We offer competitive compensation packages commensurate with experience, including salary, equity, and where applicable, performance-based pay. Our Talent Acquisition Team can answer questions around dbt Labs' total rewards during your interview process. In select locations (including Boston, Chicago, Denver, Los Angeles, Philadelphia, New York Metro, San Francisco, DC Metro, Seattle, Austin), an alternate range may apply, as specified below.
  • The typical starting salary range for this role is: $197,000 - $239,000 USD
  • The typical starting salary range for this role in the select locations listed is: $219,000 - $266,000 US
Equity Stake

Benefits - dbt Labs offers:
  • Unlimited vacation (and yes we use it!)
  • 401k w/3% guaranteed contribution
  • Excellent healthcare
  • Paid Parental Leave
  • Wellness stipend
  • Home office stipend, and more!
*Equity or comparable benefits may be offered depending on the legal limitations
Our Hiring Process (All Video Interviews)
  • Interview with a Talent Acquisition Partner (30 Mins)
  • Technical Interview with Hiring Manager (30 Mins)
  • Team Interviews with Cross Collaborators ( 4 rounds, 45 Mins each)