✓
🎬 Intro
View profile
Clean data in the right place at the right time is not automatic — it is the result of well-designed pipelines that handle schema changes, API failures, and upstream data quality issues without losing records or silently corrupting downstream tables. Post your ETL job on RemoteAI and hire a developer who builds pipelines that work reliably in production, not just in the happy path.
Pre-vetted talent pool
These are the types of ETL developers available on RemoteAI — all pre-vetted, confirmed profiles.
Which systems you are pulling from (APIs, databases, SaaS tools), the target warehouse, the transformation logic needed, and the expected refresh frequency — real-time, hourly, or daily.
Not generic Python or SQL developers but practitioners who have built reliable pipelines with your specific source systems and target warehouse, including error handling and idempotent load strategies.
Look for candidates who understand schema evolution, idempotent loads, and alerting — not just the happy-path transformation. Production pipelines fail; the question is whether they fail loudly or silently.
RemoteAI charges nothing on contracts. The agreed rate goes directly to your ETL developer.
Hiring a etl developer remotely starts with a clear, well-scoped job post. This guide covers what to include, how RemoteAI's matching works, and what you can expect at each step of the process.
ETL developers on RemoteAI design and implement data integration pipelines across the full stack: extracting from REST APIs, databases, SaaS applications (Salesforce, HubSpot, Stripe), and file systems; transforming data using SQL, Python, or dbt; and loading into data warehouses (Snowflake, BigQuery, Redshift) or operational databases. Modern ETL work increasingly uses ELT patterns with tools like Fivetran, Airbyte, and dbt. Strong ETL developers choose tools based on the specific integration — managed connectors for standard SaaS sources, custom Python extractors for non-standard APIs, and SQL transforms in dbt for maintainability and testability.
A well-structured job post attracts the right etl developers and filters out irrelevant applications. Here is the exact process to follow on RemoteAI.
Which systems you are pulling from (APIs, databases, SaaS tools), the target warehouse, the transformation logic needed, and the expected refresh frequency — real-time, hourly, or daily.
Not generic Python or SQL developers but practitioners who have built reliable pipelines with your specific source systems and target warehouse, including error handling and idempotent load strategies.
Look for candidates who understand schema evolution, idempotent loads, and alerting — not just the happy-path transformation. Production pipelines fail; the question is whether they fail loudly or silently.
RemoteAI charges nothing on contracts. The agreed rate goes directly to your ETL developer.
Looking to browse talent directly?
View vetted ETL Developer Jobs and contact them directly — no job post needed.
Data sources (APIs, databases, SaaS tools), target warehouse, transformation tools (dbt, SQL, Python), refresh frequency, expected data volume, and whether this is a new pipeline build or maintenance of existing ones.
ETL transforms data before loading; ELT loads raw data first and transforms in the warehouse. ELT with dbt has become the modern default for cloud warehouses (Snowflake, BigQuery) because warehouse compute is cheap and SQL transforms are more maintainable. ETL is still appropriate for heavy transformations that should not run in the warehouse or for real-time processing requirements.
Free. No listing fee, zero commission on contracts.
ETL developers on RemoteAI typically charge $60–$140/hour. dbt, Fivetran, and Airbyte specialists with complex integration experience are at the higher end.
Sign up free and describe the sources, destination, transformation logic, and refresh frequency. RemoteAI matches your post to data pipeline specialists with relevant integration experience. Applications typically arrive within 24 hours.