Senior QA Engineer - Data Operations (Automation & Manual Testing) at Arthur J. Gallagher and Co.

Colombo, Western Province, Sri Lanka -

Full Time

Start Date

Immediate

Expiry Date

09 Aug, 26

Salary

0.0

Posted On

11 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Quality Validation, Operational Testing, SQL, ETL Testing, Automation Testing, Data Pipeline Validation, Regression Testing, Defect Identification, Data Reconciliation, Agile/Scrum, Cloud Data Platforms, BI Tools

Industry

Insurance

Description

Introduction At Gallagher, we help clients face risk with confidence because we believe that when businesses are protected, they’re free to grow, lead, and innovate. You’ll be backed by our digital ecosystem: a client-centric suite of consulting tools making it easier for you to meet your clients where they want to be met. Advanced data and analytics providing a comprehensive overview of the risk landscape is at your fingertips. Here, you’re not just improving clients' risk profiles, you’re building trust. You’ll find a culture grounded in teamwork, guided by integrity, and fueled by a shared commitment to do the right thing. We value curiosity, celebrate new ideas, and empower you to take ownership of your career while making a meaningful impact for the businesses we serve. If you’re ready to bring your unique perspective to a place where your work truly matters; think of Gallagher. Overview At Gallagher, we are united by a commitment to excellence and innovation. As a Senior QA Engineer – Data Operations, you’ll play a pivotal role in ensuring the quality and reliability of our enterprise data platforms. Based in Sri Lanka, this role offers the opportunity to collaborate with a global team, contribute to cutting-edge data solutions, and make a meaningful impact on our organisation’s success. We are looking for a detail-oriented professional who thrives in a collaborative environment and is passionate about data quality, operational testing, and automation. If you’re ready to champion The Gallagher Way and help shape the future of data operations, we’d love to hear from you. How you'll make an impact In this role, you’ll be at the forefront of ensuring the integrity and reliability of our data systems. You’ll work closely with Data Engineering, DevOps, Business Intelligence (BI), and business stakeholders to implement robust quality controls and scalable testing practices. Your day-to-day responsibilities will include: Collaborating with cross-functional teams to support DataOps activities and resolve data issues. Performing data quality validation, operational testing, and defect identification to ensure seamless data operations. Conducting regression testing and validating hotfixes, break-fix changes, and data pipelines. Writing and executing SQL scripts for data validation and reconciliation. Supporting the automation of data pipelines using tools like DBT, Dataiku, and Airflow. Contributing to the development of reusable frameworks for data quality checks and automated testing. Communicating quality status and risks to stakeholders and maintaining test documentation and dashboards. About you Here’s what you’ll bring to the role: A degree in Computer Science, Software Engineering, Information Systems, or equivalent professional experience. 3-5+ years of experience in data-centric testing or Quality Assurance role, including ETL processes, data warehouses, and data transformations. Proficiency in SQL and familiarity with data validation tools like QuerySurge, Selenium, or Python-based frameworks. Knowledge of cloud data platforms (e.g., Snowflake, Azure Synapse) and BI tools (e.g., Power BI, Tableau). Strong collaboration, problem-solving, and communication skills. Experience working in Agile/Scrum environments. Preferred: QA certifications (e.g., ISTQB) and familiarity with AI/ML-based testing tools.

Responsibilities

Ensure the integrity and reliability of enterprise data platforms through quality controls and scalable testing practices. Collaborate with cross-functional teams to support DataOps, execute SQL scripts for validation, and automate data pipelines.