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Dbt Elt Jobs (NOW HIRING)

PCC Ltd

Staff Data Engineer

Salt Lake City, UT · On-site

EHR data experience a strong plus.- Proven hands-on dbt, ELT, and rETL -- shipped and maintained.- Experience moving quality to the source: data contracts, producer-side enforcement, schema ...

Anblicks

Sr Snowflake DBT Engineer

Dallas, TX · On-site

$113K - $136K/yr

Build and optimize ELT/ETL pipelines to ingest, transform, and load large-scale data from multiple sources. * Develop reusable and modular dbt models, macros, tests, snapshots, and documentation.

New

WHOOP

Product Analyst

Boston, MA · On-site

... dbt, ELT workflows) and visualization tools (Hex, Sigma, Amplitude, Looker) is a plus. • Product sense: think about the member experience, not just the numbers. • Curiosity about how things work ...

Overture Partners

ETL/ELT Developer - Pipeline

$52.25 - $68.25/hr

Design, develop, test, and implement ETL/ELT solutions using FiveTran, DBT, and Snowflake to support regulatory reporting and historical data integrations. * Develop and maintain code for data ...

Blue Cross of Idaho

dbt Engineer

Meridian, ID · On-site

$118K - $177K/yr

Build and maintain optimized ELT/ETL pipelines within Snowflake using dbt, focusing on efficient SQL transformations, materializations (tables, views, incremental models), and performance tuning.

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How much do dbt elt jobs pay per year?

As of Sep 14, 2026, the average yearly pay for dbt elt in the United States is $63,449.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,500.00 and $70,000.00 per year, depending on experience, location, and employer.

What is a dbt elt?

A DBT ELT developer is a data professional who uses DBT (Data Build Tool) to design, build, and manage data transformation workflows within the ELT (Extract, Load, Transform) process. Their role involves writing modular SQL queries to transform raw data into analytics-ready datasets, ensuring data quality, and maintaining documentation. DBT ELT developers often collaborate with data engineers and analysts to create reliable data pipelines, automate testing, and streamline deployment processes in modern data warehouses.

How does a dbt elt professional typically collaborate with data engineers and analysts within a data team?

A DBT ELT professional works closely with data engineers to ensure that raw data is efficiently loaded into the warehouse and that transformation pipelines are reliable and scalable. Collaboration with analysts is also frequent, as the DBT ELT role often involves translating business requirements into data models and ensuring that transformed data meets analytical needs. Regular communication, code reviews, and joint troubleshooting sessions are common, fostering a collaborative environment where feedback and improvements are encouraged. This teamwork helps maintain data quality, streamline workflows, and align outcomes with business goals.

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

To excel as a DBT ELT Engineer, you need strong SQL skills, experience with data modeling, and a solid understanding of ETL/ELT concepts, often supported by a degree in computer science or a related field. Familiarity with DBT, cloud data warehouses like Snowflake or BigQuery, and version control systems such as Git is typically required. Attention to detail, problem-solving ability, and effective communication are valuable soft skills in this role. These competencies ensure accurate data transformation, maintainability, and reliable collaboration within data engineering teams.

What is the difference between Dbt Elt vs Data Engineer?

AspectDbt EltData Engineer
CredentialsSQL, Data Modeling, Dbt certificationsSQL, Python, Cloud certifications
Work EnvironmentData teams, analytics projectsData pipelines, infrastructure
Industry UsageBusiness analytics, BIData infrastructure, ETL processes

While both roles involve working with data, Dbt Elt focuses on transforming data within analytics workflows using tools like dbt, primarily in BI and analytics teams. Data Engineers build and maintain data pipelines and infrastructure, often working on larger-scale data systems. Dbt Elt specialists typically have skills in SQL and data modeling, whereas Data Engineers require programming and cloud platform expertise. Understanding these differences helps organizations assign the right roles for their data projects.

What other helpful pages are available for Dbt Elt?

Other pages related to Dbt Elt:

Infographic showing various Dbt Elt job openings in the United States as of September 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 20% Physical, 1% Hybrid, and 79% Remote job distribution, with an average salary of $63,449 per year, or $30.5 per hour.

Staff Data Engineer

Salt Lake City, UT • On-site

PCC Ltd
See more jobs at PCC Ltdexternal

Full-time

Posted 24 days ago

Job description

About MetabodyYour body runs continuously. Your care runs on appointments -- fifteen minutes against half a million minutes of signal a year. The data piles up in apps nobody reads between visits, and by the time anyone looks, the window has closed.Metabody closes the loop. We unify every signal -- wearables, labs, records -- into one longitudinal graph; our AI co-clinician reads it continuously and surfaces what matters; and a licensed provider in any of 50 states is ready to act. Not just a wearable. Not just telehealth. The whole loop, compounding with every outcome.We're early, with real patients across all 50 states and a founding team that's built, shipped, and scaled before. This is a founding-team hire: you'll own a function from day one and set the patterns the next ten people inherit.The RoleYou build the longitudinal graph the entire company -- and the AI co-clinician -- reads from. A doer role: more time in the pipeline than in meetings about it. Stand up the lakehouse with quality enforced where data enters, and PHI handled correctly from the start.What you'll do- Build the longitudinal health graph end to end -- wearables, labs, records, FHIR-native integrations -- with clean PHI separation.- Shift quality left: data contracts at ingestion, bad rows quarantined loudly.- Own the ELT and rETL pipelines; shrink what they have to clean up.- Make the numbers governed and agent-ready: metric definitions in version-controlled code with lineage.- Direct AI agents on real pipeline work daily -- spec, review, decide what an agent may fix alone.What we're looking for- Strong EDW and data lake/lakehouse fundamentals in production -- Databricks ideally.- Healthcare PHI/HIPAA experience; EHR data experience a strong plus.- Proven hands-on dbt, ELT, and rETL -- shipped and maintained.- Experience moving quality to the source: data contracts, producer-side enforcement, schema registries.Source: https://careers.metabody.ai/open-roles/staff-data-engineer

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