• Design, document, and maintain Axiom's enterprise data model, ensuring coherence and consistency across disparate systems and platforms. • Establish and enforce data governance policies, data quality standards, and associated assurance mechanisms to ensure the reliability and integrity of organizational data assets. • In coordination with the VP, Enterprise Applications, define and maintain the data architecture roadmap, including effort scoping, dependency identification, and alignment with enterprise technology strategy. • Directly manage the Data Engineer; provide technical mentorship, set priorities, and support professional development. • Serve as the primary data architecture liaison to the Product, Operations, and Data Science functions. • In coordination with the VP, Enterprise Applications, evaluate and determine the technology stack for AI solutions and other data initiatives. • Collaborate with the VP, Enterprise Applications and Integrations Lead to reconcile roadmap priorities and ensure integration-produced data meets enterprise data model standards. • Participate collaboratively in the design and implementation of Model Context Protocol integrations, enabling AI tooling to access Axiom's information assets. • Administer and govern the Databricks environment in coordination with the Data Engineer. • Establish and maintain data documentation standards: entity definitions, lineage, ownership, and access policies.

Role Description This role at Arbitration Forums is as unique as it is rewarding because of the AF IPAAL Values (Integrity, Passion, Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion). The Data Catalog Specialist drives and supports our data governance initiatives and ensures the integrity, quality, and security of our organization's data assets. This role is responsible for defining, implementing, and managing our data cataloging and metadata management practices as part of our overall data governance program. This role is an SME for AF in the areas of data classification, cataloging, lineage harvesting and plotting, and metadata, contributing to the quality and security of our data, ensuring that data assets are documented, discoverable, and accessible for utilization in advanced analytics, data science, machine learning, and AI-powered applications. Departmental Expectation of Employee - Adheres to AF Policy and Procedures and the AF IPAAL Values and TRI Model - Acts as a role model within and outside AF - Performs duties as workload necessitates - Maintains a positive and respectful attitude - Communicates regularly with the departmental leader about department issues - Demonstrates flexible and efficient time management and ability to prioritize workload - Consistently reports to work on time, prepared to perform duties of the position - Meets Department productivity standards Essential Duties and Responsibilities - Develop, implement, and maintain strategies for data discovery, cataloging, and metadata management - Ensure that the quality of the data cataloged meets company standards and adheres to internal guidelines - Curate and validate metadata for integrity and accuracy, ensuring that taxonomies and structures are captured to provide additional context - Maintain clear lineage information and establish source of truth for data items, including mapping and reconciliation of information - Work with data owners to ensure that taxonomies are aligned with business definitions - Define and measure the key performance indicators (KPIs) associated with data cataloging and lineage, identifying deviations and recommending corrective actions - Enable effective data stewardship and accountability through the definition of supporting processes and implementation of procedures in cataloging tools - Lead and drive to completion efforts to capture and maintain metadata, including data lineage, data quality, and data usage information - Provide guidance to employees on data governance and cataloging processes and procedures, as well as training on the data governance tool stack - Raise awareness of data management best practices and their importance to business operations - Foster a culture of data stewardship, collaboration, and continuous improvement - Monitor compliance with data governance policies and assess effectiveness of controls - Prepare and present data governance reports, dashboards, and metrics to senior leadership Qualifications - Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or a related field - 6 years of experience in data cataloging tools and platforms - In-depth understanding of metadata management principles and practices, as well as strong working knowledge of frameworks, processes, and tools for data lineage plotting and harvesting - Strong understanding of data governance principles, frameworks, and best practices - Familiarity with regulatory requirements and industry standards related to data privacy and security - Technical Skills: - Proficiency in data modeling, database design, and data warehousing (e.g., SQL, NoSQL, Hadoop, MS Azure cloud, etc.) - Understanding of cloud-based data platforms (Snowflake, Databricks) - Experience with ETL/ELT tools and data integration technologies (e.g., Apache, DBT, Informatica, Matillion, Talend) - Working knowledge of cloud services (i.e., MS Azure, AWS, Google Cloud) - Strong understanding of data catalogs and lineage plotting practices and tools (Unity, Purview) - Familiarity with data visualization and reporting tools (e.g., Webfocus, Power BI) - Proficiency in programming languages such as Python or R - Soft Skills: - Excellent analytical and problem-solving abilities - Strong communication and interpersonal skills to collaborate with cross-functional teams - Ability to lead projects and mentor junior staff - Auto Insurance claims industry experience preferred Americans with Disability Specifications Physical Demands The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is occasionally required to stand; walk; sit; use hands to finger, handle, or feel objects, tools, or controls; reach with hands and arms; climb stairs; balance; stoop, kneel, crouch or crawl; talk or hear; taste or smell. The employee must occasionally lift and/or move up to 25 pounds. Specific vision abilities required by the job include close vision, distance vision, color vision, peripheral vision, depth perception, and the ability to adjust focus. Work Environment This is a fully remote position requiring reliable high-speed internet access and a dedicated workspace. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Design and implement robust, scalable data pipelines to meet various business and analytics team needs. • Integrate and process large volumes of data from diverse sources (structured and unstructured). • Contribute to defining and standardizing data engineering best practices and ensure data quality and integrity. • Develop automation solutions for data ingestion, transformation and provisioning routines. • Support business areas with technical solutions aimed at democratizing data (self-service BI, catalogs, data models). • Actively participate in agile ceremonies and collaborate with multidisciplinary teams across data, product and technology. • Document processes, data flows and technical standards to promote reuse and scalability.

• Design and develop data ingestion pipelines from external sources (ETLs, APIs, relational and non-relational databases, files, telemetry sensors, etc.); • Integrate and consolidate data from different sources within the Azure environment, ensuring data quality and consistency; • Implement reference architecture for data processing and storage; • Create and manage data lakes, data warehouses, and data marts within the Azure ecosystem; • Develop and optimize ETL/ELT processes using Microsoft tools such as Azure Data Factory, Databricks, Synapse Analytics, and Azure Functions; • Ensure governance, security, and scalability of data pipelines; • Monitor and optimize data load performance, identify bottlenecks, and propose improvements; • Work closely with data scientists and functional analysts to meet business needs.