Data Architect

Job Title: Data Architect - Commercial Real Estate Insurance Experience

Job Locations: US-TX-Dallas US-IL-Chicago

Duration- 6 months

Overview

Currently, we are on the lookout for a seasoned Data Architect, specialized in commercial real estate insurance. This critical role focuses on the creation and stewardship of a sophisticated data platform, emphasizing extensive data and dimensional modeling expertise to underpin advanced risk management and insurance procurement strategies.

Key Responsibilities

Advanced Data Modeling: Develop and refine complex data models that accurately represent the nuances of insurance risk management. Employ dimensional modeling techniques to enable scalable and performance-optimized analytics.

Strategic Architecture Development: Design a data architecture that not only supports immediate needs but is also adaptable to future challenges in insurance risk assessment and mitigation.

Collaboration for Innovation: Engage with risk management and insurance experts to deeply understand their data analysis needs, providing tailored data modeling solutions that enhance decision-making processes.

Governance and Data Quality: Implement rigorous data governance frameworks to ensure the accuracy, completeness, and security of insurance and risk management data. Uphold high standards of data quality across all data assets.

Platform Enhancement: Continuously assess and evolve the data architecture to incorporate emerging technologies and methodologies, ensuring the platform remains at the forefront of industry standards.

Effective Communication: Serve as the key intermediary between IT, risk management, and insurance teams, facilitating clear and effective communication of data strategies and their business impacts.

Desired Qualifications

Education: Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.

Professional Experience: Minimum of 7 years in a data architect role, with a significant focus on data and dimensional modeling. Experience in the insurance or risk management sector is highly preferred.

Technical Skills: Demonstrated expertise in data and dimensional modeling, database management systems (SQL, NoSQL), ETL frameworks, and big data technologies. Knowledge of cloud data services (AWS, Azure, Google Cloud) is advantageous.

Industry Knowledge: Deep understanding of insurance industry dynamics, risk assessment practices, and the specific data challenges encountered in this sector.

Analytical and Problem-solving: Exceptional ability to analyze complex data issues and develop innovative modeling solutions.

Communication Skills: Strong verbal and written communication capabilities, with a talent for making complex data concepts accessible to non-technical stakeholders.

Leadership: Demonstrated leadership qualities with a proven track record of managing projects, guiding teams, and promoting a culture of collaboration and innovation.