Sr Manager - Data Architecture

Sr Manager - Data Architecture

This position is available to Virginia residents as Richmond or Lynchburg, VA Hybrid in-office applicants or remote applicants residing in states/locations under Eastern or Central Standard Time:
Alabama, Arkansas, Connecticut, Delaware, Florida, Georgia, Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, Minnesota, Mississippi, Missouri, Nebraska, New Hampshire, New Jersey, New York, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, Texas, Virginia, Washington DC, Vermont, West Virginia or Wisconsin.

This role is not eligible for employment visa sponsorship.

You will be designing the structural blueprints for Genworth’s data systems, ensuring that the data is secure, accessible, and available so that business goals and requirements are met with your blueprints. The blueprints will have enough detail on how data is collected, stored, integrated, transformed, and published so other teams can implement the blueprints. The blueprints you build will also contain capability frameworks so the how data is collected, stored, integrated, transformed, and published is done in a consistent manner across teams when appropriate and also with pre built components or templates to further enable a consistent approach and enable more cost effective and faster execution of data product delivery.

• Establish enterprise data models including an enterprise insurance data model that is followed by different build and vendor partners.
• Define data domains and structures based on business requirements.
• Define and enable consistent data designs so data solution construction and data user experience is consistent. Create decision trees to define what must be consistent based on the situation and requirements.
• Define and design interoperability across data solutions including the technology platforms, data pipelines, data models, ML and AI applications, data governance platforms, data security, and hyper scaler cloud services.
• Align and leverage data governance interoperability work such as leveraging data stewards for defining data model attribute names and definitions. Also, work with the data governance team on metadata information about the data model that is needed for data governance management.
• Data modeling:
  Develop conceptual, logical, and physical data models for business intelligence, AI and ML requirements, and operational data use cases.
• Performance Optimization:
  Monitor and optimize data models for query performance and scalability.

• Bachelor’s degree in computer science, Information Systems, Data Science, Mathematics, or related field. Master’s degree preferred.
• Technical qualifications
  • Minimum 3 years of experience in data modeling in a Lakehouse analytics environment.
  • Proficiency in a data modeling tool such as ER Studio.
  • Experience with big data technologies and platforms (e.g., Data Bricks, Spark, AWS, Azure).
  • Expert level in DDL and SQL development.
  • Experience working with data governance, quality frameworks, and metadata management, and how this connects to data modeling practices and needs.
• Overall qualifications
  • Strong analytical, problem-solving, and critical thinking skills needed for data modeling.
  • Excellent communication and interpersonal abilities.
  • Ability to work independently and collaboratively in a cross-functional team environment.

• Understanding of PII and PHI data and how they are governed and secured.
• Experience working on an agile team using agile tools, and associated practices.
• Data taxonomies in insurance.
• Knowledge of Azure and AWS services relevant to data architecture and services.
• Knowledge of data lakes, and data pipelines that transform raw data into the data that is required.

• Collaborating with data modelers on how their data model scope should integrate into the enterprise insurance data model.
• Participating in meetings with business stakeholders to understand analytical or operational data needs so the best data modeling approach is selected.
• Designing and…