Senior QA Lead

We are seeking a highly skilled and detail-oriented Senior QA Lead to join our team to lead and optimize the testing function, ensuring high-quality product releases by developing strategies, managing resources, and driving continuous improvement in test processes and tools.

Key Responsibilities:

• Strategic Planning and Execution: Develop and implement comprehensive Test strategies and Test best practices to align with project goals and business objectives around the T&S space.

• Team Leadership and Development: Manage and mentor a team of test engineers and QA professionals, fostering a collaborative and high-performing environment.

• Process Improvement: Identify areas for improvement in testing processes, tools, and methodologies, and implement solutions to enhance efficiency and effectiveness.

• Test Automation: Lead test automation efforts, promoting the use of automation tools and frameworks to improve test coverage and speed. Bring in the AI mindset and initiatives for continuous efficiencies at various stages of the test process.

• Collaboration and Communication: Collaborate with project managers, development teams, and other stakeholders to ensure testing efforts are aligned with project timelines and requirements.

• Quality Assurance: Ensure that testing activities comply with established quality standards and best practices and monitor and report on testing progress and quality metrics.

• Risk Management: Identify and mitigate risks related to testing processes and project deadlines.

• Data Analysis: Collect and analyze data to identify trends and areas for improvement in testing processes. Validate data integrity, transformation logic, and reconciliation between source and target systems.

• Vendor Management: Manage relationships with external vendors and suppliers, if applicable.

Must Have Skills:

• 15+ years of QA experience in Agile and Waterfall Development model managing large complex projects.

• Design, develop, and execute comprehensive test strategies, test plans, and test cases for ETL and data migration projects.

• Ability to strategize, develop and execute E2E testing capability at a practical level.

• Experienced in Azure Dev Ops and setting up Test Management Tools related to requirements traceability, test plans, test labs, and defects management.

• Experienced in various types of testing – support for Unit, Smoke/Sanity, Functional, System, SIT, Integration, regression, support UAT etc.

• Experience in creating a scalable framework design which can be applied in a generic way across multiple teams.

• Troubleshoot issues with team members implementing test frameworks and guide with a 'hands-on' approach where necessary.

• Should be willing to do hands-on testing as required.

• Ensuring Test Delivery Assurance complies with established standard tools and framework.

• Strong written and verbal communication skills; ability to communicate well across the entire organization.

• Working closely with Product Managers, developers, business analysts, designers and testers to understand requirements and translate them into effective test frameworks.

• Effectively coach team members to build understanding of test strategy and create both automated and manual test frameworks to support testing best practice.

• High level of familiarity with testing at strategy level and able to provide advice rooted in experience regarding Functional, Regression, and Interface/Integration testing along with UAT support.

• Ability to plan and strategize testing for complex systems, which involves planning scope, Release/Sprint planning, resource planning, and overall planning for E2E testing activities.

• Capable of designing and executing detailed functional test cases for complex requirements.

• Proactive and organized, capable of working in an ambiguous/uncertain environment, understanding risks and flagging them on time, as well as mitigating risks while ensuring quality deliverables adhere to timelines.

• Excellent communication, coordination skills, and stakeholder management.

• Experienced virtual team worker with capability to work across time, geographical, and cultural boundaries.

• Leadership skills and ability to drive change using influence and networking.

• Great team player and effective leader with a long-term vision.

• Experience in identifying and implementing process improvements that enhance delivery and discover optimization opportunities.

• Evidence of routinely 'going the extra mile' in building testing processes and knowledge within the team.

Technical skill set:

• Proven technology champion in working with relational databases, data warehouse databases, and query authoring (SQL), along with familiarity with a variety of databases.

• Highly experienced in building and optimizing complex queries and adept at manipulating, processing, and extracting value from large, disconnected datasets.

• Proven experience in working with data engineering technologies and ADLS, ADF, Azure Databricks, Azure SQL, Synapse, and SAP HANA. Handling big data sets and technologies will be an asset.

• Validation of large-scale datasets and big data processing workflows.

• Proven champion with in-depth knowledge of scripting languages like Python, SQL, Spark-SQL, and PySpark.

• Development and enhancement of automated test suites using Python, SQL, PySpark, or Spark SQL.

• Collaboration with Data Engineers, Architects, and Business Analysts to ensure data solutions meet business requirements.

• Very good understanding of data foundation initiatives, including modeling, data quality management, data governance, data maturity assessments, and data strategy in support of key business stakeholders.

• Previously created or enhanced CI/CD build and release pipelines.

• Experience with visualization tools like PowerBI and QlikSense to validate data visualizations, dashboards, and reports.

• Ensuring reporting accuracy and consistency across data analytics platforms.

• Support for business users with UAT and production validation activities.

• Knowledge in data science (AI/ML, NLP, GenAI, Agentic AI).

Education: Bachelor's degree in computer science or a related field, or equivalent experience.

Certifications: Relevant testing certifications (e.g., ISTQB) are a plus.