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Dbt Data Engineer Jobs in Wisconsin (NOW HIRING)

Lead Forward Deployed Engineer - AWS

Milwaukee, WI · On-site

$101K - $133K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

... Developer to help build and support high-quality data solutions across the firm. In this role, you ... Experience with data integration tools such as SSIS, Fivetran, dbt, Azure Data Factory, or similar ...

Principal Data Architect

Milwaukee, WI · Hybrid

$160K - $190K/yr

... engineering * Strong expertise in SQL and relational databases (SQL Server preferred) * Strong experience with Snowflake * Experience building data pipelines using DBT (3+ years preferred) * 5+ years ...

... Apache Spark, dbt, Delta Lake, Apache Iceberg, Cloud AI Platform, Spring, and React ... engineering experience with data warehouses, data lakes or software engineering with a data ...

Senior Software Engineer - Data

Madison, WI

$123K - $162K/yr

The Role We are looking for a Senior Software Engineer to drive the evolution of our shared data ... Hands-on experience with batch-style data workflows using tools like dbt, Airflow, or similar ...

DBT experience preferred * Analytics engineering or data engineering experience preferred * Familiarity with with ETL/ELT methodologies * Experience with cloud data warehouses (Snowflake, Redshift ...

DBT experience preferred * Analytics engineering or data engineering experience preferred * Familiarity with with ETL/ELT methodologies * Experience with cloud data warehouses (Snowflake, Redshift ...

Showing results 21-40

Dbt Data Engineer information

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

To thrive as a Dbt Data Engineer, you need strong SQL skills, experience in data modeling, and a solid understanding of ELT/ETL pipelines, often supported by a degree in computer science or a related field. Familiarity with dbt (data build tool), version control systems like Git, and cloud data platforms such as Snowflake or BigQuery is typically required. Attention to detail, problem-solving abilities, and effective collaboration are essential soft skills for this role. These skills ensure robust, scalable, and maintainable data transformations that drive reliable analytics and business insights.

How does a dbt data engineer typically collaborate with data analysts and other stakeholders?

As a Dbt Data Engineer, you'll work closely with data analysts, business intelligence teams, and sometimes product managers to translate business requirements into reliable, well-structured data models. Collaboration often involves reviewing transformation logic, ensuring data quality, and providing documentation or training on Dbt models. You may also participate in regular stand-ups or data modeling sessions to align on priorities and address data challenges collaboratively. Effective communication skills are key, as you'll bridge the gap between raw data and actionable insights.

What is a dbt data engineer?

Dbt Data Engineers are professionals who specialize in using dbt (data build tool) to transform, test, and document data within modern data warehouses. They build and maintain data pipelines by writing SQL-based transformation scripts and ensuring data quality through automated testing. Dbt Data Engineers collaborate closely with analytics teams to create reliable, well-documented datasets that support business intelligence and analytics initiatives.

What is the difference between Dbt Data Engineer vs Data Analyst?

AspectDbt Data EngineerData Analyst
Primary FocusBuilding and maintaining data transformation pipelines using dbtAnalyzing data to generate reports and insights
Skills & ToolsSQL, dbt, ETL pipelines, cloud platformsSQL, Excel, BI tools, data visualization
Work EnvironmentData engineering teams, cloud data platformsBusiness units, reporting teams
CertificationsSQL, cloud certifications, dbt trainingData analysis, visualization certifications

While both roles work with data and SQL, Dbt Data Engineers focus on developing scalable data transformation pipelines using dbt, whereas Data Analysts primarily analyze data to produce reports and insights. The roles complement each other within data teams but differ in technical scope and responsibilities.

What are popular job titles related to Dbt Data Engineer jobs in Wisconsin? For Dbt Data Engineer jobs in Wisconsin, the most frequently searched job titles are:
What cities in Wisconsin are hiring for Dbt Data Engineer jobs? Cities in Wisconsin with the most Dbt Data Engineer job openings:

Senior Data Analyst (Hybrid - Madison or Austin)

Zendesk

Madison, WI

$86K - $109K/yr

Full-time

Posted 8 days ago


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.