Data QA Engineer – Enterprise Data
T
TruelogicTechnology Services
LatAmFull-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLETLMicrosoft Power BIJiraTableauTestRailSelenium
Requirements
- Advanced ability to write and execute complex SQL queries for deep data verification, reconciliation, and troubleshooting.
- Proven track record of validating ETL and ELT data pipelines, transformation logic, and complex data warehousing environments.
- Hands-on experience testing database objects and structures, with a solid understanding of data normalization and schema validation.
- Practical experience documenting full-lifecycle test plans, cases, results, and defects in tools like JIRA or TestRail.
- Hands-on experience with test automation tools and programming languages such as Python, Selenium (with SQL assertions), or custom database scripting is highly preferred.
- Familiarity with non-functional testing using tools like Apache JMeter for database load, stress, and performance testing is a plus.
- Experience testing presentation layers, reports, and business logic in BI platforms such as Tableau or Power BI is strongly desired.
- Understanding of query execution plans, indexing strategies, and database performance tuning is a plus.
Responsibilities
- Ensure data accuracy, consistency, and completeness across pipelines by thoroughly validating ETL processes, referential integrity, constraints, and data normalization.
- Perform comprehensive functional testing on core database objects, including stored procedures, triggers, views, and functions.
- Validate data migrations and write complex SQL queries to verify data correctness and system integrity.
- Test data pipelines, transformations, and business logic within business intelligence reporting tools like Tableau and Power BI to guarantee accurate report generation.
- Build and maintain automated test scripts to execute seamless database regression and integration testing.
- Identify slow-running queries, monitor execution plans, evaluate database indexing, and collaborate closely with DBAs to fine-tune overall system performance.
- Partner with developers, data analysts, and product teams to track defects utilizing JIRA or TestRail and drive data quality best practices across the engineering organization.
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