Sdet Engineer

Job Summary:

We are seeking a meticulous and technically skilled Data QA Engineer to ensure the accuracy, reliability, and performance of our data platforms and pipelines. The ideal candidate will have strong expertise in SQL, data profiling, ETL testing, and data quality validation, and will work

closely with data engineers, analysts, and business stakeholders in an Agile environment.

Key Responsibilities:

• Develop, document, and execute comprehensive test plans, test cases, and test strategies for complex data solutions.
• Ensure quality is embedded throughout the data lifecycle, from source to target.
• Work within an Agile/Scrum framework and actively participate in sprint planning, stand-ups, reviews, and retrospectives.
• Collaborate closely with data engineers and analysts to build quality from the start.
• Perform data validation, data profiling, and end-to-end ETL testing.
• Verify data accuracy, completeness, consistency, and correctness across pipelines.
• Design test scenarios that validate data quality rules, business logic, transformations, and integrations.
• Identify, log, track, and document defects with clear root-cause analysis.
• Collaborate with engineering teams to ensure timely resolution.
• Plan and execute performance and load testing for data pipelines and platforms.
• Ensure scalability, efficiency, and adherence to business SLAs.
• Clearly communicate test results, data quality risks, and issues to both technical and

non-technical stakeholders.

Qualifications and Skills:

• 4+ years of experience in a dedicated Data QA Engineer, ETL Tester, or Data Quality Analyst role.
• Strong understanding of QA methodologies (Agile, Waterfall) and the full Software Testing Life Cycle (STLC).
• Hands-on experience in data validation, data profiling, and ETL testing.
• Expert-level SQL skills for querying, analysis, and data validation.
• Proven ability to design data-driven test cases covering complex data risks.
• Strong problem-solving skills with the ability to independently troubleshoot data

anomalies.

• Meticulous focus on data accuracy, integrity, and consistency.
• Excellent communication skills and ability to work effectively in a cross-functional team.

Preferred Skills:

• Cloud Platforms: Familiarity with Google Cloud Platform (GCP), including BigQuery and Cloud Run.
• Data Warehousing: Knowledge of dimensional modeling, star schemas, and data warehousing concepts.
• Automation: Experience with test automation frameworks or scripting for data validation and testing.