Data Architect - Hybrid

For over a century, the Workers' Compensation Insurance Rating Bureau of California (WCIRB) has been California's trusted, objective provider of actuarially based information and research, advisory pure premium rates and educational services integral to a healthy workers' compensation system. The WCIRB is a California unincorporated, private, nonprofit association comprised of all companies licensed to transact workers' compensation insurance in California. The operations of the WCIRB are funded primarily by membership fees and assessments; no state money is used to fund its operations. The WCIRB is a stable company and a proven leader in the workers’ compensation insurance industry nationwide.

The WCIRB performs a number of functions to accurately measure the cost of providing workers' compensation benefits and ensure a healthy workers’ compensation system. To learn more about our company, please visit About Us | WCIRB California. The WCIRB employs approximately 175 people with the average tenure of over 10 years. We are committed to fostering a healthy, safe and diverse work environment leading to a dedicated, collaborative and innovative workforce This is a hybrid position where approximately 40% of the work time is spent at the home office in Oakland, California.

The role of the Data Architect is to expand the company’s use of data as a strategic enabler of corporate goals and objectives. The Enterprise Data Architect will achieve this by strategically designing, developing, and implementing data models for enterprise-level applications and systems. These models shall be architected at the following layers: conceptual, logical, business area, and application. This individual will act as the primary advocate of data modeling methodologies and data processing best practices.

Essential Duties and Responsibilities

Strategy and Planning

• Serve as a liaison between Enterprise Architecture and the Data Management Team for all data products. Understand all data sets and where the data resides and how it is being used
• Evaluate new data sets and determine the best approach for integrating them with existing data or the data warehouse
• Develop blueprints for Data Models, Data Flows, Data Lakes, and Data Warehouse that can efficiently support current and future business needs
• Analyze the flow of data across systems and departments and optimize how data is utilized by our customers, actuaries and applications
• Enhance data infrastructure and mechanisms to assist research and development to utilize both internal and 3rd party data
• Develop and deliver long-term strategic goals for data architecture vision and standards in conjunction with data users, department managers, clients, and other key stakeholders.
• Create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap.
• Establish processes for governing the identification, collection, and use of corporate metadata; take steps to assure metadata accuracy and validity.
• Establish methods and procedures for tracking data quality, completeness, redundancy, and improvement.
• Ensure the success of enterprise-level application rollouts

Operational Management

• Assess and determine governance, stewardship, and frameworks for managing data across the organization.
• Develop and promote data management methodologies and standards.
• Select and implement the appropriate tools, software, applications, and systems to support data technology goals.
• Oversee the mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality.
• Collaborate with project managers and business unit leaders for all projects involving enterprise data.
• Identify and resolve data-related problems related to systems integration, compatibility, and multiple-platform integration.
• Act as an advocate of data management, including coaching, training, and career development to staff.
• Develop and implement key components as needed to create testing criteria in order to guarantee the fidelity and performance of data architecture.
• Document the data architecture and environment in order to maintain a current and accurate view of the larger data picture.
• Identify and develop opportunities for data reuse, migration, or retirement.
• Lead the adoption of cloud-based solutions for data storage and processing to ensure scalability and cost effectiveness.