Summary:
At Pearson we ‘add life to a lifetime of learning’ so everyone can realise the life they imagine. We do this by creating vibrant and enriching learning experiences designed for real-life impact. Pearson was founded in 1844 and has been built on our ability to grow with and adapt to a constantly evolving market. Our employees are dedicated to creating high-quality, digital-first, accessible and sustainable resources for lifelong learning.
About the job:
The Data Quality Engineer operates at IC20 level as an individual contributor within delivery teams, supporting the build and operation of data integration platforms. The role focuses on ensuring the reliability, accuracy and consistency of data flowing through the Technical Hub and downstream systems.
This role sits within a data integration function supporting an Azure-based Technical Hub, with data pipelines spanning ingestion, transformation and distribution layers, alongside event-driven integration with downstream platforms.
Working closely with Data Engineers, Integration Engineers and platform teams, the Data Quality Engineer is responsible for validating data transformations, implementing automated data quality checks, and supporting reconciliation processes to ensure data integrity across systems.
About You: You have experience working in data-focused QA or data engineering environments, with a strong focus on validating data pipelines and ensuring data quality at scale.
You are comfortable working hands-on with SQL and automated validation frameworks and can investigate data issues across complex pipelines. You understand how data flows across ingestion, transformation and distribution layers and can work closely with engineering teams to resolve defects.
You bring a structured, detail-oriented approach to testing and are focused on automation over manual validation wherever possible.
Key Responsibilities
Design and implement data validation checks across ingestion, transformation and distribution pipelines
Develop automated data quality tests to validate canonical data transformations
Implement reconciliation processes between the Technical Hub and downstream platforms
Validate event-driven data propagation and ensure completeness and correctness
Monitor pipelines for data integrity issues, missing records and unexpected changes
Investigate and support resolution of data quality issues with engineering teams
Define and maintain data quality metrics and dashboards
Contribute to testing strategy (unit, integration and end-to-end validation of data flows)
Support data replay, recovery and backfill validation during incidents
Embed data validation into CI/CD pipelines where possible
Key Skills & Experience
Strong SQL skills for validation, reconciliation and analysis
Experience building automated data validation rather than relying on manual data checks
Hands-on experience with automated data testing approaches (e.g. pytest or similar frameworks)
Experience validating ETL / ELT pipelines and transformations
Experience in data QA, data quality engineering, or testing data pipelines
Understanding of data quality dimensions (accuracy, completeness, consistency, timeliness)
Experience working with event-driven or integration-based systems
Strong analytical and problem-solving skills
Data Quality and Testing
Data & Integration
Azure Data Factory (ADF)
SQL (T-SQL)
DevOps & Tooling
GitHub
Visual Studio Code
Jira
Basic CI/CD awareness
Desirable Skills & Experience
Experience in data integration or platform-based environments
Exposure to canonical data models and data standardisation
Experience with data observability or monitoring tools
Understanding of data lineage and traceability
Experience working in Agile delivery environments
Azure certification is beneficial
Great Expectations
Soda / Soda SQL
dbt (tests)
Azure Service Bus (topics, queues)
Event-driven integration patterns
Azure Monitor / Log Analytics / Application Insights
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Who we are:
At Pearson, our purpose is simple: to help people realize the life they imagine through learning. We believe that every learning opportunity is a chance for a personal breakthrough. We are the world's lifelong learning company. For us, learning isn't just what we do. It's who we are. To learn more: We are Pearson.
Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing [email protected].
Job: Engineering
Job Family: TECHNOLOGY
Organization: Assessment & Qualifications
Schedule: FULL_TIME
Workplace Type: Hybrid
Req ID: 23963
