Data QA Analyst

Job Role: Senior Data QA Analyst- Implementation & Modernization
Location: Hyderabad
Experience: 5+ Years
Job Role Summary
The QA Analyst/Tester supports the implementation and delivery of cloud-based marketing database solutions built on Snowflake and Databricks across AWS, Azure, and GCP environments. This role is responsible for validating data pipelines, transformations, business rules, integrations, and reporting outputs to ensure high-quality and reliable marketing data solutions. The QA Analyst uses test tools, test methodology, best practices and standard quality assurance processes to deliver functional, deployable, supportable and maintainable products and services. The role documents, communicates and suggests remedies for disputed issues/defects using defined standards, working with cross functional teams in highly collaborative manner. The ideal candidate has strong analytical skills, experience testing data platforms, and an understanding of cloud-based data architectures.
Duties & Responsibilities
Execute end-to-end testing and data validation for cloud-based marketing database implementations, including ingestion, transformation, curation, and reporting layers within modern data architectures.
Develop, document, and execute test strategies and detailed test plans for cloud-based marketing data solutions.
Validate requirements and design documentation for testability and document gaps or risks
Validate ETL and ELT processes built in Snowflake, Databricks, and cloud-native services across AWS, Azure, and GCP.
Execute functional, integration, system, regression, and user acceptance testing.
Validate data accuracy, completeness, consistency, and integrity across large-scale datasets.
Perform advanced SQL-based validation to reconcile source-to-target mappings and confirm business rule implementation.
Create and manage test data required to validate functional and technical requirements.
Test identity resolution, segmentation logic, campaign audience outputs, and marketing activation datasets.
Validate model score deployments and ensure correct application of business logic within curated datasets.
Perform comprehensive defect lifecycle management, including documentation, prioritization, retesting, validation of fixes, and follow-through across all test cycles.
Collaborate with data engineers, architects, business analysts, and project managers to clarify requirements and ensure alignment.
Support performance and scalability testing for high-volume data environments.
Participate in code reviews and design discussions to ensure testability and quality standards are met.
Maintain organized documentation of test execution results, metrics, and evidence within appropriate testing tools.
Contribute to automation of test cases and development of reusable validation frameworks where applicable.
Support release validation, production readiness testing, and post-production verification.
Ensure adherence to data governance, security, and compliance requirements.
Qualifications Required
Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or related field.
3+ years of experience in QA or testing roles supporting data engineering, analytics, or marketing database solutions.
Advanced knowledge of testing methodologies and QA processes.
Strong SQL skills, including ability to validate medium to high complexity queries, joins, aggregations, and transformations.
Experience testing data pipelines in Snowflake and/or Databricks environments.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Understanding of ETL and ELT processes and modern cloud data architectures.
Experience using defect tracking and collaboration tools such as Jira, SharePoint, Confluence, or similar platforms.
Ability to read and understand technical design documents and data models.
Strong ability to investigate data issues and perform root cause analysis independently.
Strong written and verbal communication skills.
Strong organizational skills and attention to detail.
Ability to adapt quickly to changing priorities in fast-paced environments.
Strong teaming skills and emotional intelligence.
Preferred Qualifications
Experience with automated testing tools or frameworks, including TestRail or similar platforms.
Exposure to data privacy, governance, and compliance standards in marketing data environments.
Experience with dbt transformations, orchestration tools such as Dagster or Airflow, and CI/CD pipelines.
Certifications in Snowflake or Databricks

Work arrangement
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