Key Responsibilities
- Collaborate closely with business leaders technical teams and vendors to understand business goals processes and data needs ensuring architectural decisions are business-aligned.
- Translate business objectives into data architecture requirements partnering with technical staff to assess feasibility and execution.
- Define and guide the agencys enterprise data architecture including the creation and ongoing maintenance of enterprise data flows with a focus on how data moves across systems to support core business operations analytics and decision-making.
- Provide direction and oversight for the design of data solutions while leveraging technical staff to execute on specific implementation details and configurations.
- Ensure understanding application and enforcement of enterprise data standards across systems and teams.
- Recommend phased approaches to integrating new data sources and platforms in alignment with the agencys modernization roadmap and long-term data strategy.
- Lead data integration and migration planning to ensure accurate and efficient transitions between systems.
- Collaborate with data stewards and data owners to provide regular updates on project progress and status.
- Develop and maintain documentation on data architecture data flows and data models to ensure clarity and consistency.
- Contribute to data governance frameworks that ensure data quality consistency and compliance with relevant policies and regulations.
- Provide updates to leadership on architecture progress risks and contributions to agency-wide data and modernization efforts.
- Contribute to and help evolve the agencys enterprise data strategy ensuring it supports both current needs and future growth.
Knowledge Skills and Experience
- Experience in pension retirement or benefit distribution systems including health insurance and related data processes
- Proficient in creating and maintaining Data Flow Diagrams (DFDs)
- Experience enforcing enterprise data standards and managing enterprise vs. local data usage
- Experience working with both transactional data models and applications as well as data lake architectures and solutions
- Proficiency with ERwin Data Modeler for developing documenting and maintaining logical and physical data models in support of enterprise architecture.
- Strong business acumen with the ability to understand synthesize and translate business needs into high-level data architecture strategies.
- Ability to collaborate with technical teams in the implementation of architecture relying on their expertise for detailed solution design and execution.
- Extensive experience leading data efforts in complex multi-system environments with a focus on integration and business impact.
- Deep understanding of enterprise data management disciplines: data governance master data metadata lineage and quality.
- Knowledge of data architecture principles reference architectures and best practices for both on-premises and cloud-based solutions.
- Experience with data modeling tools and working with technical staff who focus on data integration technologies.
- Strong communication and collaboration skills with the ability to engage with business and technical stakeholders at all levels.
- Strategic mindset with attention to data enablement not just system architecture.