Lead Quality Engineer - Automation & Manual, Data Domain

Introduction


Overview

At Gallagher, we are united by a commitment to excellence and innovation. As a Quality Engineer Lead – Data Operations, you’ll play a pivotal role in ensuring the quality and reliability of our enterprise data platforms.

Based in Sri Lanka, this dual-function role offers the opportunity to lead a team, support business-critical data operations, and embed quality engineering practices into ongoing development.

This is your chance to work with a global team, contribute to cutting-edge data solutions, and make a meaningful impact on our organisation’s success.

How you'll make an impact

In this role, you’ll lead quality engineering efforts for both production support and development activities. You’ll ensure business-critical data remains reliable in production while embedding quality practices into ongoing development. Day-to-day, you’ll:

• Act as the primary Quality Engineering (QE) contact for Data Operations and support teams.
• Mentor and guide QA engineers, ensuring high-quality deliverables and best practices.
• Oversee defect triage, root cause analysis, and data issue resolution.
• Lead testing for new data pipelines, transformations, schema changes, and reporting enhancements.
• Define and enforce data quality rules, validate ETL/ELT pipelines, and ensure critical reports are accurate.
• Write and review SQL scripts for validation and reconciliation.
• Contribute to pipeline automation using tools like DBT, Dataiku, and Airflow.
• Establish reusable frameworks for data quality checks and automated testing.
• Define quality gates for deployments and data releases while 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 experience.
• 6-8+ years of experience with a strong focus on data-centric testing, including ETL processes, data warehouses, and data lakes.
• 3+ yeares in a QE Lead or SME role for data platforms
• 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.
• Preferred: QA certifications (e.g., ISTQB) and familiarity with AI/ML-based testing tools.

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