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Dbt Developer Jobs in Virginia (NOW HIRING)

Computer Enterprises, Inc.

Data Engineer

Richmond, VA · On-site

$100K - $120K/yr

The Senior Data Engineer drives and implements data engineering best practices, ensures high ... Hands-on experience with enterprise ETL/ELT platforms (e.g., Talend, dbt, Informatica). * Deep ...

Deloitte

Lead Forward Deployed Engineer - AWS

Richmond, VA · 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 ...

Deloitte

Senior Forward Deployed Engineer- AWS

Richmond, VA · On-site

$103K - $142K/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 ...

Deloitte

Senior Forward Deployed Engineer- AWS

Mclean, VA · On-site

$105K - $145K/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 ...

Deloitte

Lead Forward Deployed Engineer - AWS

Mclean, VA · On-site

$103K - $136K/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 ...

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All JobsDbt Developer JobsDbt Developer Jobs in Virginia

Dbt Developer information

See Virginia salary details

$16

$52

$81

How much do dbt developer jobs pay per hour?

As of Aug 14, 2026, the average hourly pay for dbt developer in Virginia is $52.39, according to ZipRecruiter salary data. Most workers in this role earn between $40.05 and $64.09 per hour, depending on experience, location, and employer.

What is the difference between Dbt Developer vs Data Engineer?

AspectDbt DeveloperData Engineer
Primary FocusBuilding and maintaining data transformation pipelines using dbtDesigning, developing, and managing data infrastructure and pipelines
Skills & CertificationsSQL, dbt, data modeling, analytics skillsSQL, Python, ETL tools, cloud platforms, data architecture
Work EnvironmentAnalytics teams, data warehouses, BI projectsData platforms, cloud environments, big data systems

While both roles involve working with data, a Dbt Developer specializes in transforming data using dbt within analytics and BI projects, whereas a Data Engineer focuses on building and maintaining the broader data infrastructure and pipelines across various systems.

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

To thrive as a DBT Developer, you need strong SQL expertise, data modeling skills, and experience with ETL processes, typically supported by a background in computer science or data engineering. Familiarity with DBT (Data Build Tool), version control systems like Git, and cloud data warehouses such as Snowflake or BigQuery is essential. Attention to detail, problem-solving abilities, and effective communication help you deliver scalable data solutions and collaborate with cross-functional teams. These skills are crucial for building reliable data pipelines, ensuring data quality, and enabling data-driven decision-making within organizations.

What is a dbt developer?

A Dbt Developer is a data professional who specializes in using dbt (data build tool) to transform raw data into clean, reliable datasets for analytics and business intelligence. They write modular SQL code to perform data transformations, manage data models, and ensure data quality within modern data warehouses. Dbt Developers collaborate closely with data engineers, analysts, and business users to create efficient, maintainable data workflows. Their work enables organizations to make informed decisions based on trustworthy and well-structured data.

How does a dbt developer typically collaborate with data engineers and analysts on a project?

DBT Developers frequently work alongside data engineers to ensure that data pipelines provide clean, reliable data to downstream users. They collaborate with analysts to understand data requirements, define business logic, and implement transformations that support analytics and reporting. Regular communication is essential for aligning on naming conventions, documenting models, and troubleshooting issues. This collaboration often takes place through code reviews, shared documentation, and agile ceremonies such as sprint planning or stand-ups.

What are popular job titles related to Dbt Developer jobs in Virginia?

For Dbt Developer jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Dbt Developer jobs in Virginia look for?

The top searched job categories for Dbt Developer jobs in Virginia are:

What cities in Virginia are hiring for Dbt Developer jobs?

Cities in Virginia with the most Dbt Developer job openings:

Dbt Developer jobs near you
Infographic showing various Dbt Developer job openings in Virginia as of August 2026, with employment types broken down into 82% Full Time, 4% Part Time, and 14% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $108,962 per year, or $52.4 per hour.

Data Engineer

Computer Enterprises, Inc.

Richmond, VA • On-site

$100K - $120K/yr

Other

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Data EngineerRichmond, VA 23219 (hybrid)
Pay: $100,000-120,000
Role Summary

The Senior Data Engineer is a hands-on expert and technical leader, actively engaged in designing, building, and optimizing scalable, reliable data pipelines at an enterprise level. This role not only guides architectural decisions but also directly implements advanced ELT solutions, troubleshoots complex data challenges, and ensures best practices through practical, high-impact contributions.

This role combines deep hands-on expertise with technical ownership, mentoring, and architectural alignment. The Senior Data Engineer drives and implements data engineering best practices, ensures high standards for quality and security, and partners with architecture and platform teams to improve the overall data ecosystem.

Required Skills & Experience
  • Advanced expertise in SQL, ELT patterns, and performance tuning.
  • Strong experience with Oracle Exadata, Snowflake or similar cloud/on-prem data warehouses.
  • Hands-on experience with enterprise ETL/ELT platforms (e.g., Talend, dbt, Informatica).
  • Deep understanding of data warehousing architecture and dimensional modeling.
  • Experience designing and supporting large-scale, production data pipelines.
  • Strong scripting experience (Python, shell).
  • Experience with data virtualization tools (e.g., Denodo, Composite, Dremio, Starburst).
  • Experience with DataOps practices, CI/CD, and observability.
  • Required 5 to 7+ years of Data Engineering experience.
  • ETL development and process support; may require weekend/off-business-hours work.
Key Responsibilities
  • Build end-to-end data pipelines and ETL/ELT solutions to support analytics, reporting, and AI/ML use cases.
  • Apply scalable patterns for batch and incremental processing by developing, testing, and deploying data workflows.
  • Review and implement data modeling, transformation logic, and performance strategies.
  • Evaluate, select, and integrate tooling, frameworks, and platform capabilities.
  • Build complex, high-volume data pipelines using SQL-centric ETL/ELT patterns.
  • Design and implement scalable streaming pipelines to process real-time data.
  • Lead performance tuning efforts across pipelines, warehouses, and workloads.
  • Ensure data pipelines are resilient, observable, and production ready.
  • Implement enterprise-grade error handling, restartability, and monitoring.
  • Build and maintain scalable, low-latency streaming data pipelines using Kafka, Kinesis, or Spark Streaming.
  • Perform on-the-fly data cleaning, validation, and enrichment.
  • Utilize indexing and partitioning strategies to optimize warehouse and big data environments.
  • Implement standards for data quality checks, validation, and reconciliation.
  • Ensure pipelines meet security, access control, and governance requirements.
  • Partner with governance and DataOps teams on metadata, lineage, and auditability.
  • Improve operational monitoring, alerting, and incident response processes.
  • Identify reliability, performance, and cost optimization opportunities.
  • Support production troubleshooting and root cause analysis.
  • Investigate data quality incidents and identify design/coding gaps.
  • Participate in design and code reviews.
  • Partner with infrastructure teams, application teams, and architects on complex transformations.
  • Translate ambiguous requirements into technical solutions.
  • Work across complex multi-platform environments.
Behavioral Expectations
  • Delivering at Pace
  • Collaborative Teamwork
  • Effective Communication
  • Ownership and Adaptability
  • Ability to Work Independently
  • Achievement Orientation
  • Self-Starter
  • Concern for Quality
  • Flexibility
Preferred Qualifications
  • Experience supporting AI/ML or advanced analytics pipelines.
  • Cloud platform experience (AWS, Azure, or GCP).
  • Prior experience influencing enterprise data standards or reference architecture.
  • Experience optimizing cost and performance in cloud data warehouses.
  • Hands-on experience with Cribl, Apache Kafka, Kafka Connect, Spark Streaming, or Apache Flink.
Education
  • Bachelor''s Degree or higher required
  • Computer Science, Information Systems, Mathematics, or related discipline
Preferred Industry Background
  • High preference for candidates with large-scale utility industry experience.
  • Will also consider candidates supporting large-scale capital projects.
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