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Dbt Analytics Jobs in Madison, WI (NOW HIRING)

Apply best practices in dimensional modeling to create robust and scalable data models for analytics and reporting. * Leverage tools such as Python, dbt, and SQL to develop advanced data ...

... analytics solutions. * Deep expertise designing and optimizing modern data integration and enterprise-scale ETL/ELT solutions using Fivetran and dbt. * Strong experience designing and supporting ...

... analytics solutions. * Deep expertise designing and optimizing modern data integration and enterprise-scale ETL/ELT solutions using Fivetran and dbt. * Strong experience designing and supporting ...

Dbt Analytics information

See Madison, WI salary details

$37.8K

$64.4K

$92.7K

How much do dbt analytics jobs pay per year?

As of Aug 18, 2026, the average yearly pay for dbt analytics in Madison, WI is $64,391.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,400.00 and $71,500.00 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.
Infographic showing various Dbt Analytics job openings in Madison, WI as of August 2026, with employment types broken down into 1% Internship, 92% Full Time, 3% Part Time, and 4% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $64,391 per year, or $31 per hour.

Senior Data Analyst (Hybrid - Madison or Austin)

Zendesk

Madison, WI • On-site

$86K - $109K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Job DescriptionAbout us

We are looking for a Senior Data Analyst to support the Foundation Insights team. You will work cross-functionally to help drive analytics, enablement, and data-driven decision-making for our global engineering and product teams. Foundation Insights at Zendesk owns operational data for Engineering and Product Development - measuring productivity, reliability, AI adoption, cost/OpEx, and infrastructure excellence.

In this role, you will turn raw engineering, product, and operational data into trusted metrics, self-service dashboards, and analyses that leaders act on. You'll own analytical domains end-to-end - from the SQL and dbt models that define a metric, to the interactive dashboards stakeholders read, to the definitions and documentation that keep everyone aligned. You'll work across a modern data stack - Snowflake, dbt, Airflow, GitHub, and AI platforms like Claude, Codex and MCP servers - and your work will directly shape how Product Development measures and improves itself.

Location

This hybrid role requires working from our Madison, WI or Austin, TX office at least two days per week or as determined by your manager.

What you'll do:
  • Develop SQL queries and dbt models to transform engineering and operational data into trusted, analysis-ready data models
  • Build and maintain self-service dashboards and reports that put engineering productivity, AI adoption, reliability, and cost metrics in front of engineers and leaders up to the VP+ level
  • Define and standardize metrics across engineering teams - owning the semantics of what a metric means (funnel stages, eligibility, DORA definitions like change-failure-rate and cycle time) so comparisons stay valid
  • Measure platform adoption, AI tool usage, and ROI across engineering, and communicate findings through a thoughtful combination of quantitative analysis and qualitative storytelling
  • Proactively conduct analyses and investigations that identify insights into underlying engineering and business matters - digging into data anomalies and asking "why" until you understand root causes
  • Write clear documentation and enablement material so stakeholders can self-serve and trust the data
  • Build relationships and collaborate with internal engineering, product, and enterprise data and analytics teams - reviewing peers' work and aligning on shared definitions
  • Implement data quality tests, monitoring, and validation (e.g. dbt tests, Monte Carlo) to ensure accuracy and prevent invalid metric comparisons
  • Help integrate data from APIs and third-party tools into Snowflake for analytics and AI enrichment
What you bring to the role:Basic Qualifications:
  • 3+ years of experience in the analytics or data space, delivering analyses and metrics that drive decisions
  • Proven proficiency in SQL - comfortable with complex queries and transforming data into analysis-ready models
  • Hands-on experience with dbt (or a strong willingness to ramp quickly)
  • Experience with data visualization / BI or dashboarding tools (e.g. Tableau, Looker)
  • Experience with a cloud data warehouse (e.g. Snowflake, BigQuery, Redshift, Databricks)
  • Internally motivated, self-starter with an analytical and curious mindset - you find insights and show the value of data-driven decision-making
  • Ability to work cross-functionally and communicate technical concepts to both technical and non-technical audiences, up to the executive level
  • Detail-oriented with a passion for data quality, problem solving, and reliable, well-defined metrics
Preferred Qualifications:
  • Proficiency in Python and familiarity with data modeling, forecasting, and data analysis techniques.
  • Experience developing and deploying open source BI solutions
  • Familiarity with software engineering best practices - Git/GitHub PR workflows, code review, CI/CD, and testing
  • Background working with large datasets, data APIs, and cloud object storage (AWS/GCP), plus data quality monitoring tools (Monte Carlo, dbt tests)
  • Fluency with modern AI tooling (Claude, GPT/Codex, MCP servers, AI agents) and experience embedding AI-assisted workflows into analytics work.
  • Knowledge of engineering productivity metrics - DORA metrics, PR review cycles, deployment frequency, incident management KPIs
The US annualized base salary range for this position is $151,000.00-$227,000.00. This position may also be eligible for bonus, benefits, or related incentives. While this range reflects the minimum and maximum value for new hire salaries for the position across all US locations, the offer for the successful candidate for this position will be based on job related capabilities, applicable experience, and other factors such as work location. Please note that the compensation details listed in US role postings reflect the base salary only (or OTE for commissions based roles), and do not include bonus, benefits, or related incentives.

The intelligent heart of customer experience

Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.

Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.

As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.

Zendesk is an equal opportunity employer, and we're proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here.

Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to peopleandplaces@zendesk.com with your specific accommodation request.