Remote ETL Quality Assurance Engineer

Overview

Remote
$65
Contract - W2
Contract - Independent

Job Details

We’re hiring an ETL QA Engineer to perform SQL-based data validation, ETL testing, and quality assurance across large healthcare datasets. This position supports end-to-end ETL pipelines, source-to-target verification, data mapping, Snowflake/AWS workflows, and API testing to ensure high-quality data movement for new client implementations.
 

Type: 6-Month Contract (Full-Time)

Start Date: January 5, 2026

Location: 100% Remote (Local Nashville candidates preferred)

Compensation: 60/hr
 

Key Responsibilities

ETL Testing & SQL Data Validation

• Test ETL (extract, transform, load) processes end-to-end.

• Validate source-to-target data mappings and transformation logic.

• Write and run SQL queries (joins, aggregations, data validation).

• Perform reconciliation checks, boundary tests, and negative testing across large datasets.

 

Data Quality, Sub-File Creation & Analysis

• Create and validate sub-files using Excel, Access, Studio 3T, and data analysis tools.

• Review datasets to confirm expected business rules and client requirements.

• Ensure consistent file formatting across multiple client implementations.

 

Data Setup & Data Processing

• Support file creation, application setup, and manual data preparation.

• Validate datasets for accuracy before downstream workflows.

 

Cloud, API & ETL Workflow Support

• Review AWS Lambda logs and cloud workflows (as needed).

• Validate API calls using Postman.

• Run Snowflake queries and support cloud-based ETL validation.
 

Documentation & Collaboration

• Create ETL test cases and document QA results.

• Log defects with detailed replication steps.

• Partner with ETL developers, business analysts, and onshore/offshore QA teams.

Required Skills

• 2–5+ years of ETL QA, data testing, or data analysis experience.

• Strong SQL skills (joins, aggregations, data validation queries).

• Experience with Excel, Access, Studio 3T, Notepad++, or similar data tools.

• Understanding of ETL pipelines, data mapping, and data transformation.

• High attention to detail and strong problem-solving skills.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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