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Dbt Data Engineer Jobs in Arizona (NOW HIRING)

Cynet Systems

Data Engineer

Tucson, AZ · On-site

$110.40K - $132.60K/yr

Technical Lead, Data Engineering We are seeking a Technical Lead, Data Engineering with strong hands-on expertise in Snowflake-based cloud data warehousing and modern ELT development using dbt (Core ...

Cynet Systems

Data Engineer

Phoenix, AZ · On-site

$113.70K - $136.50K/yr

Data Engineering Manager Design, develop, and maintain scalable, production-grade ELT pipelines using Snowflake and dbt (Core or Cloud). Lead technical design discussions and provide architectural ...

VBeyond

Lead Data Engineer

Phoenix, AZ · On-site

$113.70K - $136.50K/yr

Role Overview The Lead Data Engineer will serve as a technical leader responsible for defining data ... Lead the development of ELT pipelines using Qlik Replicate, Snowflake, dbt Cloud, and CI/CD tools

Axon

Senior Data Engineer II (Hybrid)

Scottsdale, AZ · On-site +1

$106.80K - $145.10K/yr

Hands-on expertise with Snowflake, dbt, Fivetran, and modern ELT/data warehouse architecture ... Proficiency leveraging AI-powered engineering tools such as Cursor and Claude Code as part of day ...

Axon

Senior Data Engineer II (Hybrid)

Scottsdale, AZ · On-site

$107.20K - $145.70K/yr

Hands-on expertise with Snowflake, dbt, Fivetran, and modern ELT/data warehouse architecture ... Proficiency leveraging AI-powered engineering tools such as Cursor and Claude Code as part of day ...

Axon

Senior Data Engineer II (Hybrid)

Scottsdale, AZ · On-site

$107.20K - $145.70K/yr

Hands-on expertise with Snowflake, dbt, Fivetran, and modern ELT/data warehouse architecture ... Proficiency leveraging AI-powered engineering tools such as Cursor and Claude Code as part of day ...

Axon

Senior Data Engineer II (Hybrid)

Scottsdale, AZ · On-site

$106.80K - $145.10K/yr

Establish and evolve engineering best practices, including dbt conventions, data modeling patterns ... testing standards, CI/CD workflows, and documentation practices. * Evaluate and introduce new tools ...

E-Solutions

Data engineer (ETL/ELT)

Phoenix, AZ · On-site

... Dbt /snowflake Preferred skills Informatica Detailed We are seeking a Technical Lead, Data Engineering with strong hands-on expertise in Snowflake-based cloud data warehousing and modern ELT ...

Cuboid IT Solutions

Senior Data Engineer

Phoenix, AZ · On-site

$105.20K - $143K/yr

Phoenix, AZ Design Data Engineering capabilities that cater to the enterprise and span multiple ... or dbt Labs. - Excellent verbal and written communication skills to effectively present complex ...

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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 are Dbt Data Engineers?

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.

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Dbt Data Engineer jobs near you
Infographic showing various Dbt Data Engineer job openings in Arizona as of May 2026, with employment types broken down into 15% Full Time, 67% Part Time, 2% Temporary, 15% Contract, and 1% Nights. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.
Population Health Data Engineer

Population Health Data Engineer

Software Technology Inc

Paradise Valley, AZ • On-site

$115.80K - $139K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Population Health Data Engineer

We are seeking a skilled Population Health Data Engineer with deep expertise in Epic data ecosystems and healthcare analytics. This role will focus on designing, building, and optimizing data pipelines and models to support population health, quality of care and claims analytics.

Key Responsibilities
  • Design, develop, and maintain scalable data pipelines supporting population health, claims analytics, and reporting.
  • Work extensively with Epic data sources including Registries, Rosters, Chronicles, Clarity, and Caboodle.
  • Integrate clinical and claims data to support longitudinal patient views and advanced analytics.
  • Develop data models for population health use cases including quality measures, risk stratification, utilization, and care management analysis.
  • Support development and operationalization of risk scoring data models and analytics (e.g., MARA, HCC, RAF).
  • Process and transform healthcare claims data (medical and pharmacy) for analytics and reporting.
  • Work with Milliman MedInsight data structures to support payer-provider analytics and efficiency benchmarking.
  • Build and optimize ELT pipelines using modern cloud platforms.
  • Collaborate with healthy planet, efficiency, quality, clinical, and analytics teams to translate business needs into technical solutions.
  • Ensure data quality, governance, and compliance with healthcare regulations (e.g., HIPAA).
  • Optimize performance of large-scale datasets and queries.
Required Qualifications
  • Strong hands-on experience with Epic systems, including:
    • Epic Registries
    • Chronicles data structures
    • Hyperspace or Hyperdrive environments
    • Clarity and Caboodle data models
  • Experience with modern data engineering tools and platforms:
    • Snowflake (data warehousing)
    • DBT (data transformation and modeling)
    • Dynamic Tables in Snowflake
  • Solid understanding of healthcare domain concepts, including population health and value-based care.
  • Experience with healthcare claims processing (medical and pharmacy claims).
  • Hands-on experience with Milliman MedInsight data models and analytics workflows.
  • Strong SQL and data modeling expertise.
  • Experience building and maintaining data pipelines.
Key Skills
  • Population Health & Risk Analytics
  • Healthcare Data Modeling (Clinical and Claims)
  • Epic Data Ecosystem Expertise
  • Snowflake & DBT
  • SQL & Performance Optimization
  • Data Governance & Compliance
Education & Experience
  • Bachelor’s or Master’s degree in Computer Science, Health Informatics, Data Engineering, or related field.
  • 6+ years of experience in data engineering, with strong preference for healthcare, payer, or population health analytics experience.

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