Associate Director, Data Quality

Role Summary

Associate Director, Data Quality at Vertex. Responsible for building and managing data quality platforms, processes and strategy across the enterprise. Work with data engineers, analysts, data stewards and product owners to define, implement, and optimize data quality tools, integrations, patterns and processes to enable observability and trust in data.

Responsibilities

• Develop and execute DQ capability and technology roadmaps aligned with Vertex business priorities.
• Collaborate with technology portfolio managers, governance leads and business users to identify and collect DQ technology and platform requirements.
• Develop and promote data quality frameworks, standards, and processes tailored to life sciences data.
• Enable data observability with comprehensive monitoring and issue detection across data assets.
• Leverage AI and automation to enhance data quality coverage, reduce manual effort, and accelerate remediation.
• Collaborate with Data Governance to define and deliver data quality metrics, driving continuous improvement and accountability.
• Provide guidance and training on data quality tools and methodologies to technical and non-technical stakeholders.
• Develop and manage SOPs for ongoing data quality assessment, remediation and exception handling.
• Own and maintain the DQ platforms and manage the platform strategy and roadmaps (Quality tools, Observability, Issue Lifecycle, Integration).
• Manage the technology teams running DQ technology and platforms.
• Work with DTE Compliance, Data Privacy, Data Security and Quality Assurance to ensure regulatory and lifecycle compliance.

Qualifications

• Required: Bachelor's degree (preferably in technology) and 8+ years of data engineering, data management, or related roles in life sciences or related industries.
• Required: 3+ years delivering and defining data quality capabilities and practices across functions.
• Required: Proven record building and delivering a data quality program and platform at enterprise scale.
• Preferred: Experience deploying data quality tools (Great Expectations, SODA) and platforms (Collibra DQ, Monte Carlo, Anomalo).
• Preferred: Strong background in data observability, integrations, data engineering, analytics, and data pipeline architectures.
• Preferred: Familiarity with AI/ML techniques for data profiling, anomaly detection, and automation.
• Required: Excellent analytical, problem-solving, communication, and leadership skills.
• Required: Strong written and verbal communication and presentation skills.
• Required: Experience running IT managed services or outsourced/offshore teams.
• Required: Strong Agile toolset (Jira, Bitbucket, Confluence) and MS Office skills (Project, Visio, Excel, PowerPoint).

Skills

• Data quality program design and delivery at enterprise scale
• Data observability and integration
• Data engineering, analytics, and data pipeline architecture
• AI/ML for data profiling and automation
• Leadership and stakeholder management
• Communication and presentation

Education

• Bachelor's degree required (technology discipline preferred)