Senior Data Quality Engineer, Corporate Vice President

Key Skills

Aartificial intelligence, Agile methodologies, Data science techniques, DataOps, DevOps, Effective communication skills, IT, Machine learning techniques, Microsoft-Excel, Planning and organization, Powerpoint

Job Description

Responsibilities include providing expert-level application of data quality management capabilities including profiling, defining data/information goals aligned with business priorities, implementation, and automation of operational data quality measures/KPI’s and dashboards, and data defect identification, prioritization, and remediation. The major focus is to monitor and measure quality of unstructured data, multimodal data (images, audio, video, etc.) and metadata supporting emerging Gen AI investments and use cases. The role also requires an ongoing monitoring and assessment of the quality including bias of Gen AI use case outcomes. The role requires an assessment of levels of data/information quality in the context of business needs, reporting on business impacts, finding root causes of data quality deficiencies, and making recommendations on both tactical and strategic changes to prevent future negative impacts and enable positive business outcomes

Success in the role will be measured by the degree to which foundational and emerging data quality management capabilities are employed to support the objectives of New York Life business priorities with an emphasis on emerging Gen AI use cases.

Key Accountabilities:

• Perform as a member of a team in the Chief Data Officer organization, with a concentration on the implementation of Gen AI use cases involving both structured data and unstructured information and metadata
• Fully understand and influence the definition and desired outcomes of emerging Gen AI use cases 
• Identify sources of data/information to enable emerging use cases for Gen AI, and define and execute methods to evaluate and report on quality of data/information and metadata
• Provide expert-level application of data quality management capabilities including profiling, defining data/information goals aligned with business priorities, implementation, and automation of operational data quality measures/KPI’s and dashboards, and data defect identification, prioritization, and remediation
• Assess levels of data/information quality with a focus on unstructured, multi-modal and metadata
• Monitor and assess of the quality, including bias, of Gen AI use case responses, and make recommendations to improve outcomes
• Develop and nurture effective relationships and a partnership with leaders and staff in business, technology, data strategy, data governance, data architecture, data science, ML engineering, data engineering and technology platforms ownership roles
• Assist in the development, maintenance, and promotion of data governance deliverables/assets, including data policies, data standards and data management roles and decision frameworks
• Assist in the development of Communities of Practice - virtual organizations that meet regularly to share ideas, best practices, and promote a culture where data are managed as an asset of the company
• Assist in the evaluation and reporting of emerging industry trends and technologies relevant to data management

Skills and Experience required:

• 5+ years proven experience in AI/ML or a similar role, and understanding of advanced analytics, data science and [Gen] Artificial Intelligence (AI) 
• A good understanding and passion for the role of data governance in enabling data as an asset
• Expert level proficiency and demonstrated ability with data management methodologies and technologies with an emphasis on data quality profiling, data quality rules coding, data catalogs, metadata management, and master/reference data management
• Demonstrated skills and experiences in a Data/Dev Ops role, implementing automation of data quality capabilities including data quality measures, exception handling and testing within defined and evolving data pipelines
• Demonstrated understanding and experience working in a Scaled Agile environment
• Strong proficiency to assess and understand business requirements, solve problems, and model current and future state business processes and data domains/entities
• Ability to perform basic project management functions such as project plan development and resource / time estimation of tasks
• Demonstrated ability to collaborate, communicate, build relationships, mentor and influence a community of data and technical professionals across lines of business and functional areas
• Strong written, verbal and communication skills with the demonstrated ability to work with all levels within the organization
• Ability to tell a story through presentations, to motivate and influence adoption of new ideas and capabilities
• Strong understanding of IT methodologies, functions and services
• Ability to work in a fast-paced environment and manage multiple simultaneous priorities
• Demonstrated ability to think end-to-end, connect moving parts, and anticipate and manage change impacts
• Ability to define and leverage metrics to drive performance and outcomes
• Working knowledge of MS Word, Excel, and PowerPoint
• Experience with BI/visualization tools like Tableau is desirable
• Awareness of relevant and emerging financial services / insurance data standards is desirable

Education

• Bachelor's degree in Computer Science, Data Science, AI, or a related field.
• Master's degree preferred