Senior Manager, Quality Engineering – Data

Individually we are people, but together we are Aviva. Individually these are just words, but together they are our Values – Care, Commitment, Community, and Confidence.

The Senior Manager, Quality Engineering – Data will lead and coordinate all aspects of Data Quality Engineering across Aviva’s enterprise data ecosystem. This role will own end‑to‑end quality for Aviva’s various Data Platforms, while continuing to ensure stability, accuracy, and reconciliation across technologies for BAU and various enterprise transformational initiatives. Responsibilities will be primarily program and platform related, supporting critical data initiatives spanning ingestion, transformation, analytics, reporting, and downstream system feeds.

You will work closely with Program Delivery Leads, Enterprise Data Services, Engineering, Analytics, Finance, and Business Stakeholders, as well as Quality Engineering leaders and engineers across onshore, nearshore, and offshore teams. This role is pivotal in Aviva’s QA to QE transformation, shifting data quality left, embedding automation and controls into pipelines, and providing transparency into data quality, risk, and readiness through dashboards and metrics.

As Aviva continues to modernize, data platforms and analytics are core to how we operate. We are investing in modern cloud technologies, AI ready platforms, and strong engineering practices to enable growth, efficiency, and regulatory confidence. You’ll work on exciting, diverse programs with broad exposure across IT and business teams, and you’ll have significant scope to influence how data quality is designed, measured, and sustained across the enterprise.

• Provide overall leadership for Data Quality Engineering from a platform and program perspective, covering Snowflake, Enterprise Data Hub and more.
• Define, socialize, and implement Data QE strategies and test plans aligned to Aviva’s delivery and governance frameworks.
• Establish end-to-end ownership of data quality, consolidating testing for upstream, downstream, analytics, and financial/regulatory feeds under QE accountability.
• Lead quality validation ensuring data integrity, transformation accuracy, metadata consistency, and lineage.
• Ensure robust data reconciliation including validation of synchronization processes, reports, and downstream feeds.
• Continuously look for opportunities to increase efficiency by automation and using AI.

• Define and operationalize enterprise data quality rules, profiling, anomaly detection, and benchmark frameworks.
• Embed data quality checks directly into ETL / ELT pipelines and CI/CD, enabling early detection and prevention of defects.
• Provide transparency through quality dashboards, metrics, trend analysis, and risk reporting for senior partners.

• Drive shift left, test early practices, embedding data quality validation in design, development, and pipeline stages.
• Lead adoption of automation first testing, including reconciliation automation, API‑level validation, and repeatable data validation frameworks.
• Establish Test Data Management (TDM) strategies, including masked production data, synthetic data creation, and PII‑safe data handling.

• Work with engineering and platform teams to define service health indicators, quality gates, and readiness criteria for data platforms.
• Ensure mature defect triage, incident response, and root cause analysis processes are in place for data quality issues.
• Support audit readiness through traceable evidence, controls, and documentation for data quality and testing practices.

• Lead, coach, and develop Data QE Leads and Engineers across onshore, nearshore, and offshore delivery models.
• Act as the resolution point for all data related quality risks, issues, and blockers.
• Provide regular status updates and quality insights to delivery, business, and IT leadership.

• 10+ years of hands‑on experience in Quality Engineering, with a strong focus on data platforms and data quality.
• Bachelor's…