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Dbt Data Engineer Jobs (NOW HIRING)

Capgemini

WI · On-site

$90 - $120/hr

Azure, Databricks/DBT, Data Modelling A stong plus: Collibra, Datavault Advantage: Oracle - Banking Knowledge would be ideal but is not a prerequisite.- Working Model: Our data engineer will be ...

MFS

Lead Data Engineer

Boston, MA · On-site

$124K - $149K/yr

Manage and contribute to dbt projects, ensuring code quality, proper documentation, and alignment with modular, scalable design patterns. Design, build, and administer scalable data pipelines and a ...

S Linx LLC

Sr Data Engineer

Santa Monica, CA · On-site

$128K - $154K/yr

... using DBT in Snowflake. · Work closely with analysts and business users to deliver Power BI ... for data engineering workflows. · Support data migration or integration efforts with SAP BW ...

Kanak Elite Services Inc

Data Engineer

Houston, TX · On-site

$109K - $131K/yr

DATA ENGINEER III CONTRACT LENGTH: 6 - 12 MONTH CONTRACT, LOOKING TO THEN CONVERT ONSITE 5 DAYS A ... Experience with dbt, Data Build Tool, or similar for transformation and testing. * Experience with ...

MFS Investment Management

Lead Data Engineer

Boston, MA · On-site

$124K - $149K/yr

WHAT YOU WILL DO • Develop and maintain data models in dbt (Data Build Tool) within Snowflake ... data engineering, analytical engineering and data maintenance capabilities. • Provide support ...

Co-Sourcing Partners

GCP Data Engineer

Chicago, IL · On-site

$118K - $141K/yr

GCP Data Engineer Duration: 6 months Contract to hire Location: Chicago is the preferred location ... Implement data transformation pipelines using BigQuery, dbt, and Python-based workflows. * Ensure ...

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Dbt Data Engineer information

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$44.5K

$129.7K

$177.5K

How much do dbt data engineer jobs pay per year?

As of Sep 7, 2026, the average yearly pay for dbt data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

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.

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 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.

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 the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Population Health Data Engineer

Software Technology Inc

Merrimack, NH • On-site

$117K - $140K/yr

Full-time

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.

Apply