Quality Engineer

Role Overview

A Data Testing Engineer validates data accuracy, integrity, and quality across complex pipelines, ensuring ETL processes and data warehouses function correctly. The QE is part of a multi-skilled feature team, collaborating to ensure quality and customer requirements are met when developing products.

Responsibilities

• Design and execute functional, integration, and regression tests for ETL processes, data warehouses, and data ingestion pipelines.
• Write complex SQL queries to compare source and target data; develop automated test scripts using Python, Java, or specialized tools.
• Ensure data integrity, accuracy, and completeness, including checking for data anomalies and verifying transformation logic.
• Create test plans, test cases, and documentation for defects, tracking them to resolution in tools like JIRA.
• Work with developers, data engineers, and stakeholders to understand requirements and troubleshoot data issues.
• Manage automated tests in CI/CD environments to maintain consistent quality.

Requirements

• Strong SQL skills are essential, along with experience in Python, Java, or JavaScript.
• Knowledge of dimensional modeling (star/snowflake schemas) and tools like Spark, Hive, Hadoop, or Azure.
• Experience with test automation frameworks (Selenium, PyTest) and manual testing techniques.
• Experience with GCP or any cloud technologies.
• Bachelor’s degree in Computer Science, IT, or related field.
• Typically 2–5+ years in QA or ETL testing.

Skills

• SQL
• Python
• Java
• Selenium
• GCP