Data SME

Data SME – Test Strategy & Exploratory Testing (Azure Data Platform)

Location: Bangalore

Experience Level: 5+ years in Data Testing / Data Engineering / QA

Role Summary:

We are looking for a highly skilled Data Subject Matter Expert (SME)to lead test strategy developmentand perform exploratory testingacross our data pipelines and Azure-based data platform. The ideal candidate has a strong understanding of data quality assurance, Azure services, and data lifecycle, with hands-on experience testing complex ETL/ELT workflows and ensuring data reliability, accuracy, and compliance.

Key Responsibilities:

• Define and implement comprehensive data test strategiesfor cloud-based data platforms (especially Azure).
• Conduct exploratory testingof data pipelines, transformations, and integrations to identify data quality issues and edge-case failures.
• Collaborate with data engineering and analytics teams to understand data flows, ingestion mechanisms, transformation logic, and business rules.
• Design and execute validation for:
  • Source to target data completeness and correctness
  • Schema evolution handling
  • Data transformation logic validation
  • Performance and scalability of pipelines
• Build or enhance test automation frameworksand reusable data validation scripts (SQL, PySpark, Python, etc.).
• Monitor and validate data pipeline jobs in Azure Data Factory, Databricks, Synapse, or other Azure components.
• Create test documentation: strategy docs, test plans, traceability matrices, defect reports, and sign-off criteria.
• Provide guidance and best practices around data testing, lineage tracking, data observability, and monitoring.

Required Skills & Experience:

• 5+ yearsof experience in data testing / data QA / data validation roles.
• Proven expertise in defining test strategy and QA processesfor data platforms.
• knowledge of Azure Data Services:
• Solid SQLand PySparkskills – must be able to write complex queries for validation.
• Experience in exploratory testingof data: identifying anomalies, probing logic errors, working without fully defined test cases.
• Exposure to CI/CD, test automation frameworks, version control (Git), and Azure DevOps or similar tools.
• Understanding of data modeling, data lineage, and data governance principles.
• Investment background is a plus