Associate Director, Data Quality

Job Description

General Summary:

Vertex is entering a new phase of data-driven innovation where trusted, observable, and governed data is foundational. The Associate Director, Data Quality Platform is a senior technology and product leader within the Data & Software Engineering organization, reporting to the Director, Data Governance. This role owns the enterprise Data Quality (DQ) platform strategy and execution, with an explicit mandate to build AI-first, scalable and embedded data quality capabilities across the enterprise.

The role partners closely with data stewards, data product owners, date engineering, analytics, compliance, privacy and security to translate data quality policies and standards into automated, measurable, and continuously improving platform capabilities. The Associate Director is accountable for enabling quality-by-design, reducing manual effort through AI and automation in order to enable trusted data for decision-making, regulatory use and innovation.

Key Duties and Responsibilities:

• Act as the product owner and technology lead for the Enterprise Data Quality platform by owning the vision, roadmap, prioritization and program outcomes.
• Define and execute an AI-first data quality strategy, leveraging LLMs and intelligent agents for rule generation, anomaly detection, impact analysis, root-cause identification and remediation recommendations.
• Serve as the execution lead for Data Quality within the Enterprise Data Governance Framework, translating policies, standards and control objectives into scalable platform capabilities.
• Design and govern human-in-the-loop patterns for AI-driven data quality to ensure explainability, auditability and compliance in regulated environments.
• Own and evolve data observability capabilities, including monitoring, alerting, lineage-aware impact analysis, and issue lifecycle management.
• Enable data engineers and data product teams to embed data quality controls directly into pipelines and products using standardized patterns, APIs and reusable components.
• Define and promote quality-by-design frameworks tailored to life sciences data and regulatory expectations.
• Partner with Data Governance leadership and functional councils to define quality metrics, KPIs and assurance mechanisms aligned to business risk and fitness-for-use.
• Leverage AI-assisted prioritization to focus remediation effort on the highest business, patient, and regulatory impacting issues.
• Develop and maintain SOPs for data quality assessment, remediation, exception handling and AI-assisted decisioning.
• Lead and manage technology teams and MSPs responsible for DQ platform engineering and operations.
• Collaborate with Compliance, Privacy, Security and Quality Assurance to ensure adherence to regulatory requirements and system lifecycle controls.

Knowledge and Skills:

• Demonstrated experience building and operating enterprise-scale data quality platforms in complex data ecosystems (Snowflake, Databricks, APIs, legacy platforms).
• Hands-on experience with commercial data quality and observability tools (e.g., Anomalo, Monte Carlo, Collibra) and custom-built solutions.
• Proven experience designing and deploying LLM-enabled data management or data quality solutions, including prompt engineering, agent orchestration, evaluation, and guardrails.
• Strong understanding of data observability, data engineering, analytics and pipeline architecture.
• Familiarity with data governance, cataloging, lineage and metadata management practices.
• Knowledge of AI risk management concepts including explainability, bias, validation and regulatory considerations.
• Strong product mindset with the ability to balance innovation, platform stability and operational excellence.
• Excellent leadership, communication, and stakeholder management skills.
• Experience leading internal teams and external/offshore managed services.
• Proficiency with agile and development tooling (Jira, Confluence, Bitbucket, SQL, Python).

Education and Experience:

• Bachelor’s degree required, advanced degree in technology, data, or related field preferred.
• 8+ years of experience in data engineering, data platforms, data management, or related disciplines.
• 3+ years leading enterprise data quality, observability, or data governance execution capabilities.
• Experience in life sciences or other highly regulated industries is strongly preferred.

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Pay Range:

$160,000 - $240,000

Disclosure Statement:

Flex Designation:

Hybrid-Eligible Or On-Site Eligible

Flex Eligibility Status:

In this Hybrid-Eligible role, you can choose to be designated as: 
1.    Hybrid: work remotely up to two days per week; or select
2.    On-Site: work five days per week on-site with ad hoc flexibility.

Note: The Flex status for this position is subject to Vertex’s Policy on Flex @ Vertex Program and may be changed at any time. 

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Company Information

Vertex is a global biotechnology company that invests in scientific innovation.

Vertex is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, sexual orientation, marital status, or any characteristic protected under applicable law. Vertex is an E-Verify Employer in the United States. Vertex will make reasonable accommodations for qualified individuals with known disabilities, in accordance with applicable law.

Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which the applicant has applied should make a request to the recruiter or hiring manager, or contact Talent Acquisition at ApplicationAssistance@vrtx.com