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Browse remote ETL positions — data pipeline engineering, dbt transformation layer development, and ELT workflow automation at AI-first companies.
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Posted 2 weeks ago
Senior Software Engineer, Data Platform
Boston, Massachusetts, United States; Las Vegas, Nevada, United States; Pittsburgh, Pennsylvania, United States; Remote U.S.
The Data Platform team is the vital link between our company's expansive data and the engineering teams that rely on it. We architect and operate the...
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Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowl...
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Vannevar builds AI systems for the Department of War's most consequential missions. We have 125 deployments across every branch and combatant command...
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Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems....
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We’re on a mission to make data available and actionable to everyone, everywhere. With 700+ connectors, our platform powers analytics and gives AI age...
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The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across t...
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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are en...
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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are en...
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TL;DR - We’re seeking an Analytics Engineer to own the data foundations that fuel the GTM teams: building reliable models, shaping metrics, powering a...
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At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are en...
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Role guide
What to expect in remote ETL jobs
ETL engineers build the data pipelines that make AI possible. Remote ETL jobs at AI companies involve designing ELT workflows with dbt, integrating data sources with Fivetran or Airbyte, and orchestrating pipelines with Airflow. Clean, reliable data is the most critical input for any ML system — and ETL engineers are the people who deliver it.
What you'll work on
- Build reliable ELT pipelines that feed ML training and inference systems
- Develop dbt transformations that model raw data for analytics and feature engineering
- Integrate third-party APIs and SaaS data sources into the data warehouse
- Implement automated data quality checks before ML models train on new data
What companies look for
- dbt — model development, testing, documentation, and deployment
- Modern ELT tools — Fivetran, Airbyte, or Stitch for data ingestion
- Pipeline orchestration with Airflow, Prefect, or Dagster
Frequently asked questions
What remote ETL jobs are available at AI companies?
Data engineering and analytics engineering roles focused on pipeline development. Most require SQL and dbt alongside Python and a cloud data warehouse.
Is ELT replacing ETL in remote job listings?
In modern cloud-native stacks, yes. Most AI companies use ELT — load raw data first, transform in the warehouse with dbt. Traditional ETL (transform before load) is common in legacy enterprise environments.
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