Lead Data Quality Engineer

'

: - ( - )

Experience: 7+ yrs

Location: Bengaluru, Karnataka, India

Job Type: Full-time

We are looking for an experienced Lead Data Quality Engineer to lead the design, implementation, and continuous improvement of data quality and automated testing strategies across complex data pipelines and business-critical data workflows.

The role combines data quality engineering, test automation, data engineering, technical leadership, and team development. The ideal candidate will have strong hands-on expertise in SQL and Python, experience with modern data platforms, and the ability to build scalable testing frameworks for both batch and streaming data environments.

You will play a key role in establishing robust testing practices, preventing data issues before production, and driving strategic data quality initiatives across the organisation.

Requirements

Key Responsibilities

• Lead the design and implementation of comprehensive test strategies for complex data pipelines, transformations, and business logic.
• Architect, develop, and continuously improve automated testing frameworks for batch and streaming data workflows.
• Define and establish best practices for data testing, quality validation, monitoring, and CI/CD integration.
• Develop scalable and reusable automated tests using SQL, Python, and modern data-testing technologies.
• Validate data accuracy, completeness, consistency, integrity, and business-rule compliance across large datasets.
• Partner with Data Engineers and cross-functional teams to design scalable and highly testable data solutions.
• Identify potential data-quality risks and proactively introduce controls to prevent production issues.
• Own strategic data quality initiatives from planning and stakeholder alignment through execution and measurement.
• Establish quality standards, testing methodologies, and engineering practices across data workflows.
• Evaluate and introduce new tools, frameworks, and technologies to improve test automation and coverage.
• Troubleshoot complex data-quality issues, perform root-cause analysis, and drive sustainable fixes.
• Integrate automated data testing into development and deployment pipelines.
• Monitor testing effectiveness, identify coverage gaps, and continuously improve quality processes.
• Conduct code reviews, test reviews, and technical design reviews to maintain engineering standards.
• Mentor engineers and provide technical guidance on data testing, automation, debugging, and quality engineering.
• Manage direct reports where applicable, including coaching, planning, performance support, and professional development.
• Collaborate with Product, Data, Engineering, Analytics, and other stakeholders to align quality initiatives with business objectives.
• Maintain technical documentation, testing standards, frameworks, and reusable quality assets.

What Makes You a Great Fit

• 7+ years of experience in Data Quality Engineering, Data Engineering, Software Testing, QA Automation, or a related discipline.
• Strong hands-on expertise in SQL and Python, with experience validating and analysing large-scale datasets.
• Proven experience designing and scaling automated data testing frameworks.
• Strong experience with modern data platforms and technologies such as Snowflake, Databricks, Spark, and Airflow.
• Good understanding of batch and streaming data architectures, ETL/ELT pipelines, data transformations, and data quality principles.
• Experience defining testing strategies, engineering standards, quality processes, and CI/CD practices for data workflows.
• Proven ability to lead strategic technical initiatives and drive data quality improvements across teams.
• Experience mentoring engineers, conducting technical reviews, and supporting engineering team development.
• Experience managing or leading engineering team members is desirable.
• Strong debugging, analytical, and problem-solving skills with the ability to anticipate and prevent data issues.
• Familiarity with BDD frameworks such as Behave is an advantage.
• Experience working with AWS or other cloud environments is desirable.
• Knowledge of data-quality frameworks such as Great Expectations, Deequ, or similar custom solutions is an advantage.
• Strong stakeholder-management, communication, and collaboration skills.
• Ability to balance hands-on technical execution with leadership, mentoring, and strategic ownership.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent professional experience.