Lead Data Architect

Ryan SpecialtyChicago, IL
$129,200 - $161,500

About The Position

The Data Architect will play a critical role in designing, governing, and scaling RSUM’s enterprise data ecosystem. This role is responsible for defining canonical data models (product, domain, and policy), aligning RSUM and corporate data standards, and ensuring that data architecture supports analytics, BI, and AI initiatives across the underwriting lifecycle. This role will work closely with business stakeholders, data engineering, BI/analytics, and corporate data teams to ensure the Enterprise Data Hub (EDH) serves as a reliable, scalable foundation for current and future reporting, analytics, and AI capabilities. What will your job entail?

Requirements

  • Bachelor’s degree required, Master’s degree preferred; Computer science, Information Technology, Statistics, or Engineering is preferred. Any other related discipline or commensurate work experience considered.
  • 10+ years of experience in Software/IT Architecture or related field with a Bachelor’s degree, or 8 years of experience with a Master’s degree.

Nice To Haves

  • Certified Data Management Professional (CDMP), TOGAF (The Open Group Architecture Framework) Certification, Certified Information Management Professional (CIMP), or Certified Information Systems Security Professional (CISSP) is preferred.

Responsibilities

  • Design, maintain, and govern enterprise canonical data models, including product, policy, and key domain models.
  • Ensure semantic consistency and interoperability across RSUM, corporate, and MGU systems.
  • Partner with business leaders to translate underwriting, financial, and operational concepts into scalable data structures.
  • Provide architectural oversight for data ingestion into the Enterprise Data Hub (EDH) using a modern medallion architecture.
  • Define data standards for quality, ownership, lineage, and documentation.
  • Collaborate with data engineering on schema design, transformation logic, and historical data remediation.
  • Support downstream use cases including BI reporting, advanced analytics, AI/ML, and external partner data access.
  • Act as a thought leader and steward for RSUM’s data foundations and long‑term scalability.
  • Oversees the development of data strategy and establishes data architecture principles to cater to business needs while ensuring alignment with business goals.
  • Defines data governance policies and procedures that ensure data quality, security, and compliance with regulatory requirements.
  • Oversees the design of data models and schemas to support various business functions such as policy management, claims processing, underwriting, and customer relationship management.
  • Serves as the data architecture expert and point of contact for the senior management in Data Analytics and IT, resolving technical queries and communicating technical concepts with clarity.
  • Partners with cross functional teams to ensure the team delivers effective data solutions and clearly communicates complex technical concepts to non-technical stakeholders.
  • Analyzes data requirements, designs effective database solutions, and supports policy management, claims processing, underwriting, and customer service teams in their data needs.
  • Monitors and optimizes the performance of data systems and databases to ensure efficient data retrieval and processing by identifying and resolving performance bottlenecks.
  • Oversees data integration processes to ensure seamless flow of information between different systems and platforms involving design processes, data pipelines, and data migration.
  • Develops and maintains the overall data architecture including data storage solutions, data warehousing, data lakes, and data visualization tools.
  • Collaborates with cross functional teams to understand data requirements and deliver effective data solutions communicating complex technical concepts to non-technical stakeholders.
  • Stays updated with the latest trends and advancements in data management technologies evaluating the potential impact on data architecture and recommending adoption strategies.
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