Overview

Our client, a highly successful and established organization, is seeking an experienced Lead Data Quality and Validation Engineer to spearhead critical enterprise data quality initiatives. This role focuses on owning and optimizing the quality assurance lifecycle across complex, large-scale data platforms, including data warehouse, operational data store (ODS), and modern data lake environments. You will be instrumental in maintaining the highest standards of data integrity, consistency, and reliability.

This position involves guiding a team of skilled data test professionals , collaborating intensely with engineering teams, and driving the adoption of industry-leading practices in data validation, ETL/ELT testing, and test automation. The ideal candidate is a hands-on, deeply technical expert in advanced SQL and data validation who is prepared to lead by example in a high-velocity environment.

Key Responsibilities

• Partner with development, product, and business stakeholders to implement, validate, and test complex data solutions across various heterogeneous data platforms.

• Provide technical leadership and mentorship to the team, setting standards for high-quality, efficient data testing deliverables.

• Design, develop, and execute sophisticated data validation and ETL/ELT testing strategies to guarantee the accuracy, consistency, and completeness of data flowing through complex pipelines.

• Establish, implement, and govern robust data quality frameworks, validation rules, and automated monitoring systems to ensure end-to-end trust in data assets.

• Oversee integration and data flow testing across disparate data technologies (e.g., various RDBMS and cloud-native database systems).

• Coordinate quality assurance efforts related to the presentation and consumption of data within user-facing applications (web and mobile).

• Conduct continuous analysis and reporting on quality metrics, defect trends, and overall testing performance to technical and non-technical audiences.

• Ensure the seamless integration of data quality practices and automation into the continuous integration/continuous delivery (CI/CD) development lifecycle.

• Proactively research and recommend new data technologies, tools, and testing methodologies to drive technical evolution and efficiency within the function.

Qualifications

• Bachelor’s or Master’s degree in a quantitative or technical field, or equivalent practical experience.

• A minimum of 7 years of specialized experience in data testing, QA engineering, or data engineering, including significant experience in a technical leadership or managerial capacity (2+ years) .

• Demonstrated history working with mission-critical, high-volume transactional data sets and enterprise data environments.

• Expert-level proficiency in SQL —must be able to construct and optimize highly complex queries for validation, data reconciliation, and deep analysis across various database dialects.

• In-depth understanding of data integration patterns (ETL/ELT), data orchestration, and associated scheduling tools.

• Proven hands-on experience validating data integrity and transformations across diverse storage formats, including RDBMS, NoSQL, and structured/semi-structured files (e.g., JSON, XML).

• Solid experience utilizing scripting languages, particularly Python , for complex data validation, test automation, and tooling development.

• Working knowledge of modern Agile methodologies and continuous delivery QA best practices.

• Experience overseeing quality assurance for data consumption layers, including user-facing web and mobile applications, is highly advantageous.

• Exceptional ability to communicate technical concepts clearly and manage multiple critical projects simultaneously in a fast-paced environment.