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Lead QA SDET Data Engineering

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Onsite

Lead QA SDET Data Engineering

Tavant

Lead QA SDET Data Engineering

Skills

SQL QueriesData EngineeringPythonTesting & QASnowflakeAI

2 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

2 September 2026

What they need


We are seeking a Lead QA SDET to lead automation and quality assurance efforts for our data and ETL platforms. This role owns test automation delivery using Python across Snowflake, ETL/ELT, and Informatica-based systems for a program or team, while leading a small team of Senior QA SDETs.

Roles and Responsibilities
Key ResponsibilitiesAutomation & Technical Execution

  • Design, build, and maintain Python-based automation frameworks for data and ETL validation.
  • Automate source-to-target validation, reconciliation, and transformation checks across Snowflake pipelines.
  • Build and maintain automated test coverage for Informatica ETL/ELT workflows.
  • Integrate automated test suites into CI/CD pipelines for continuous execution.
  • Review team members' automation code for quality, reusability, and maintainability.

Quality Assurance

  • Own test planning and execution strategy for the program: functional, regression, integration, and data-quality testing.
  • Validate data completeness, accuracy, consistency, uniqueness, integrity, and timeliness.
  • Manage defect lifecycle for the program: triage, prioritization, RCA on recurring/critical defects, tracking to closure.
  • Assess release readiness against defined quality gates; provide go/no-go input to leadership.
  • Maintain program-level QA dashboards (execution status, pass rate, coverage, defect aging, automation stability).
  • Identify test coverage gaps and risk areas across data flows.

Data & Domain

  • Build strong working knowledge of the program's business-critical data flows.
  • Translate business/data rules into concrete automated validation checks.
  • Partner with Data Engineers, Developers, and Business Analysts to resolve data quality issues.

Leadership

  • Lead and mentor a team of Senior QA SDETs.
  • Facilitate program-level test status and quality reviews.
  • Apply enterprise/organizational QA standards consistently within the team.
  • Use AI-assisted testing tools where appropriate, with review of AI-generated outputs.

Required Skills

Core (Mandatory):

  • Python – strong automation and framework development experience.
  • Snowflake – strong hands-on experience in data validation/warehouse testing.
  • ETL/ELT – strong understanding of pipelines and validation.
  • Informatica – solid hands-on experience with ETL workflows.
  • Strong SQL and data warehouse fundamentals.
  • Data reconciliation, transformation, and profiling experience.

Quality Assurance (Mandatory):

  • Test planning and execution across functional/regression/integration testing.
  • Defect management and RCA (program level).
  • Quality gates and release-readiness assessment.
  • QA metrics/dashboard reporting.

Preferred:

  • CI/CD and DevOps integration.
  • Cloud data platforms / data lakes.
  • API testing.
  • Exposure to AI-assisted testing tools.

Experience

Recommended: 5-8 years, including hands-on Python/Snowflake/ETL/Informatica testing experience and prior experience leading a small QA team or workstream.

Key CompetenciesCompetencyExpected LevelPython (Automation)Advanced/ExpertSQLExpertSnowflakeAdvanced/ExpertETL/ELT TestingAdvanced/ExpertInformaticaAdvancedData Quality/ValidationAdvanced/ExpertQA Test Planning & ExecutionAdvancedDefect ManagementAdvancedQuality Gates & Release ReadinessAdvancedQA Metrics & DashboardsAdvancedTeam LeadershipAdvanced

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