JB001721 Sr. Lead QA SDET Data Engineering | Bangalore · Hybrid

Techilaservices; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Techilaservices in Bengaluru, India, is seeking a Sr. Lead QA SDET to lead the Quality Engineering function for data and ETL platforms.

This hands-on automation expert defines automation strategy, sets quality standards, mentors engineers, and drives enterprise‑wide QE maturity across Snowflake, ETL/ELT pipelines, and Informatica workflows. The ideal candidate is a hands‑on automation leader who can also operate as a strategic quality advocate, guiding teams and shaping QA maturity across the

Qualifications

• Python – expert-level scripting and test automation framework design.
• Snowflake – expert hands-on data validation and warehouse testing.
• ETL/ELT – expert understanding of pipelines, transformations, and validation.
• Informatica – strong hands-on and governance-level experience.
• Strong SQL and data warehouse concepts.
• Data profiling, reconciliation, and large-scale data validation frameworks.

Responsibilities

• Architect and own the enterprise test automation framework using Python, covering data validation, ETL/ELT testing, and reconciliation.
• Set coding standards, design patterns, and reusability guidelines for the automation framework.
• Lead automation of source-to-target validation, transformation logic checks, and aggregation testing across Snowflake and downstream systems.
• Provide technical oversight of Informatica-based ETL/ELT workflows, ensuring test coverage across mappings, workflows, and sessions.
• Drive CI/CD integration of automated test suites for continuous regression and data validation.
• Resolve the most complex data quality and automation issues across teams.
• Own the overall QA strategy: test planning, design, and non-functional testing across data platforms.
• Define and enforce Quality Gates and release-readiness criteria (SIT → Regression → UAT → Production).
• Own defect management governance: triage, severity/priority standards, RCA on defects, and leakage analysis.
• Define QA metrics and dashboards for executive and operational reporting.
• Establish and govern test data and test environment standards.
• Provide independent quality sign-off and release recommendations to leadership.
• Act as the senior SME for data quality across stakeholders.
• Translate complex business rules into automated data quality checks.
• Identify enterprise-critical data flows and prioritize testing by business risk.
• Lead and mentor Lead/Senior QA SDETs.
• Facilitate quality governance forums; present risk and release readiness to leadership.
• Drive adoption of standardized QA/automation practices across teams.
• Evaluate and introduce AI-assisted testing tools with human review of AI-generated tests/scripts.

Skills

Python

Snowflake

ETL/ELT

Informatica

SQL

Data validation

Data profiling

QA automation

Tools

Devin.ai

GitHub Copilot

Job description

Technical Skills

• Batch Processes
• Database/ETL processing
• Control-M jobs
• Database transformations and stored procedures.
• Good in SQL/ PL
• Develop custom test harnesses to support Batch and Sproc validations.
• Implement AI-assisted testing capabilities utilizing Devin.ai, GitHub Copilot, and comparable approved capabilities.
• Develop automated data validation scripts, regression suites, and custom data testing harnesses.
• Python

Job Description

We are seeking a Sr. Lead QA SDET to lead our Quality Engineering function for data and ETL platforms. This is the most senior technical-leadership role in the QE organization — responsible for defining automation and testing strategy, setting quality standards across teams, and providing hands‑on technical direction for Python-based test automation across Snowflake, ETL/ELT pipelines, and Informatica workflows.

The ideal candidate is a hands‑on automation expert who can also operate as a strategic quality leader, mentoring engineers and driving enterprise‑wide QE and QA maturity.

Roles & Responsibilities

Key Responsibilities

• Automate & Technical Leadership: Architect and own the enterprise test automation framework using Python, covering data validation, ETL/ELT testing, and reconciliation.
• Set coding standards, design patterns, and reusability guidelines for the automation framework.
• Lead automation of source-to-target validation, transformation logic checks, and aggregation testing across Snowflake and downstream systems.
• Provide technical oversight of Informatica-based ETL/ELT workflows, ensuring test coverage across mappings, workflows, and sessions.
• Drive CI/CD integration of automated test suites for continuous regression and data validation.
• Resolve the most complex data quality and automation issues across teams.
• Own the overall QA strategy: test planning, test design, functional/regression/integration/non-functional testing approach across data platforms.
• Define and enforce Quality Gates and release-readiness criteria (SIT → Regression → UAT → Production).
• Own defect management governance: triage, severity/priority standards, RCA on critical defects, defect trend and leakage analysis.
• Define QA metrics and dashboards (test pass rate, coverage, automation stability, defect aging, production defect leakage, data quality score) for executive and operational reporting.
• Establish and govern test data and test environment standards.
• Provide independent quality sign-off and release recommendations to leadership.
• Act as the senior SME for data quality across business and technology stakeholders.
• Translate complex business rules into automated, measurable data quality checks.
• Identify enterprise-critical data flows and prioritize testing based on business risk.
• Lead, mentor, and set technical direction for Lead and Senior QA SDETs.
• Facilitate quality governance forums; present risk, quality, and release readiness to leadership.
• Drive adoption of standardized QA/automation practices across teams without slowing delivery.
• Evaluate and responsibly introduce AI-assisted testing tools, with human review of AI-generated tests/scripts.

Required Skills

Core (Mandatory):

• Python – expert-level scripting and test automation framework design.
• Snowflake – expert hands‑on experience in data validation and warehouse testing.
• ETL/ELT – expert understanding of pipelines, transformations, and validation.
• Informatica – strong hands‑on and governance-level experience.
• Strong SQL and data warehouse concepts.
• Data profiling, reconciliation, and large-scale data validation frameworks.

Quality Assurance (Mandatory):

• Test strategy design (functional, regression, integration, non-functional).
• Defect management and RCA at governance level.
• Quality gates and release-readiness criteria definition.
• QA/QE metrics and dashboard design.

Preferred:

• CI/CD and DevOps integration.
• Cloud data platforms, data lakes/lakehouse.
• API testing.
• AI-assisted/GenAI testing experience.