Data Test Lead

Canterr It Services; Hyderabad; Hybrid; INR 2,500,000 - 4,000,000; Full time

Job summary

Canterr It Services seeks a senior data testing leader to define and drive the end-to-end testing strategy for large-scale EDW migrations from legacy ETL platforms to cloud-native architectures.

You will oversee reconciliation, transformation validation, and complex data quality checks, with hands-on work in dbt, Azure Data Factory, and Snowflake. The role requires strong leadership and collaboration across distributed teams.

Qualifications

• 10+ years of experience in Data Warehouse and ETL Testing, including leadership responsibilities.
• Strong understanding of ETL/ELT concepts and legacy-to-cloud migration testing methodologies.
• Extensive experience in: Data validation, Transformation testing, Reconciliation testing, Source-to-target testing, Data quality assurance.
• Strong knowledge of Ab Initio components and validation of graphs, mappings, and processing workflows.
• Experience testing Azure Data Factory pipelines, orchestration flows, and metadata-driven frameworks.
• Hands-on expertise in dbt including: dbt tests, snapshots, SQL-based transformation validation, model validation, lineage verification.
• Advanced SQL expertise with modern cloud databases such as Snowflake.
• Strong understanding of dimensional modelling and enterprise data warehousing concepts.
• Experience with defect management and test management tools such as JIRA, Azure DevOps, or equivalent.
• Strong stakeholder management, communication, and leadership capabilities.

Responsibilities

• Define and lead the end-to-end data testing strategy for large-scale EDW migration programmes.
• Lead source-to-target validation and transformation validation to align with legacy rules.
• Design, develop, and automate robust data validation frameworks using dbt, SQL, and ADF.
• Validate complex transformation logic across staging, curated, and reporting layers.
• Lead and mentor distributed QA and testing teams across onsite and offshore delivery models.
• Coordinate SIT, UAT, regression, reconciliation, and production validation activities.
• Track test execution progress, defects, data quality KPIs, and reporting metrics for stakeholders.
• Build reusable frameworks for continuous data quality monitoring, automated reconciliation, and lineage validation.
• Collaborate with Data Architects, ETL Developers, Business Analysts, and Platform Teams.
• Support root cause analysis and defect triage for data discrepancies and pipeline failures.
• Ensure adherence to governance, audit, and data quality standards.

Skills

Leadership

Stakeholder management

Communication

Data testing strategy

Data validation

Transformation testing

Reconciliation testing

Source-to-target testing

Data quality assurance

Test management

Tools

Ab Initio

dbt

Azure Data Factory

Snowflake

JIRA

Azure DevOps

Job description

Key Responsibilities

• Define and lead the end-to-end data testing strategy for large-scale EDW migration programmes from legacy ETL platforms to cloud-native architectures.
• Drive source-to-target reconciliation, parallel testing, and transformation validation to ensure Azure Data Factory and dbt outputs align with existing Ab Initio processing logic and business rules.
• Design, develop, and automate robust data validation frameworks using:
  • dbt testing capabilities
  • SQL-based reconciliation techniques
  • ADF validation activities
  • Custom validation and audit frameworks
• Validate complex transformation logic, aggregations, business rules, and dimensional models across staging, curated, and reporting layers.
• Lead and mentor distributed QA and testing teams across onsite and offshore delivery models.
• Coordinate SIT, UAT, regression, reconciliation, and production validation activities.
• Track test execution progress, defect management, data quality KPIs, and testing metrics for stakeholder and programme reporting.
• Build reusable frameworks for:
  • Continuous data quality monitoring
  • Automated reconciliation
  • Data lineage validation
  • Source-to-target validation
  • Regression testing
• Collaborate closely with Data Architects, ETL Developers, Business Analysts, and Platform Teams to ensure successful migration delivery.
• Support root cause analysis and defect triage activities for data discrepancies and pipeline failures.
• Ensure adherence to enterprise governance, audit, compliance, and data quality standards.

Required Skills & Experience

• 10+ years of experience in Data Warehouse and ETL Testing, including leadership responsibilities.
• Strong understanding of ETL/ELT concepts and legacy-to-cloud migration testing methodologies.
• Extensive experience in:
  • Data validation
  • Transformation testing
  • Reconciliation testing
  • Source-to-target testing
  • Data quality assurance
• Strong knowledge of Ab Initiocomponents and validation of graphs, mappings, and processing workflows.
• Experience testing Azure Data Factorypipelines, orchestration flows, and metadata-driven frameworks.
• Hands-on expertise in dbtincluding:
  • dbt tests
  • snapshots
  • SQL-based transformation validation
  • model validation
  • lineage verification
• Advanced SQL expertise with modern cloud databases such as Snowflake.
• Strong understanding of dimensional modelling and enterprise data warehousing concepts.
• Experience with defect management and test management tools such as JIRA, Azure DevOps, or equivalent.
• Strong stakeholder management, communication, and leadership capabilities.