Middle ETL QA Engineer

Role Summary

The ETL QA Engineer is responsible for validating all extract, transform, and load (ETL) processes that support our data operations. This role focuses on end-to-end data verification, sub-file preparation, dataset creation, and ensuring each client’s unique ETL requirements are followed. The engineer collaborates closely with ETL developers, analysts, and product teams to ensure reliable, consistent, and high-quality data movement.

Key Responsibilities

ETL Testing & Data Validation

• Test ETL extract, transform, and load processes to ensure accuracy, completeness, and alignment with requirements.
• Validate source-to-target mappings, business rules, transformation logic, and workflow execution.
• Execute deep-dive data analysis using tools such as Access, Excel, Studio 3T, and occasionally DBeaver or Snowflake.
• Perform reconciliation checks, boundary tests, negative testing, and cross-system comparisons.

Data Analysis & Sub-File Creation

• Build and prepare sub files using Excel, Studio 3T, and Notepad++ based on client specifications.
• Analyze and review dataset outputs to confirm expected results for each ETL process.
• Ensure sub files are structured correctly and formatted consistently across client implementations.

Data Setup & Manipulation

• Perform data setup activities including File Sub creation, App setup, and manual data manipulation using Excel and Studio 3T.
• Validate datasets after setup to ensure they are ready for testing or downstream processes. 

Client-Specific ETL Knowledge Management

• Maintain detailed documentation of client-specific rules, processing logic, file layouts, and ETL behavior.
• Ensure each execution or validation aligns with the client’s unique requirements and variations.
• Assist in maintaining a centralized knowledge base for scalable, repeatable QA work.

API, Cloud, and Workflow Validation (As Needed)

• When applicable, perform AWS checks, including reviewing lambda execution, logs, and triggers.
• Perform API validation using Postman when ETL processes involve API integrations.
• Validate Snowflake queries and cloud data movement when required by the project.
• Access AWS and Snowflake environments sparingly and only when aligned with assigned QA responsibilities.

Test Planning & Documentation

• Create detailed test cases for ETL scenarios, transformations, and data dependencies.
• Document results, defects, and detailed reproduction steps.
• Track testing progress, data preparation steps, and client-specific variations.

Collaboration

• Work with ETL developers to troubleshoot data issues, clarify logic, and validate fixes.
• Coordinate with business analysts to ensure test coverage aligns to client expectations.
• Support both onshore and offshore collaboration, ensuring consistent QA processes across teams.

Required Skills & Qualifications

• 2–5+ years of ETL QA, data testing, or data analysis experience.
• Strong SQL skills, including joins, aggregations, and data validation queries.
• Hands-on experience with Excel, Access, Studio 3T, and general data-analysis tools.
• Experience with data-correction tools and file-manipulation utilities.
• Understanding of ETL concepts, data pipelines, and data mappings.
• Strong analytical and problem-solving skills with high attention to detail.
• Ability to track client-specific processing rules across multiple workflows.

Preferred Experience

• Exposure to Snowflake, AWS, lambda log review, or cloud-based data processing.
• Experience validating API calls with Postman.
• Experience with DBeaver or other SQL clients.
• Experience working with both onshore and offshore QA teams.

Interview stages

1. Call with recruiter
2. Technical Interview
3. Client Interview