Alvarez & Marsal - Dallas, TX
posted 2 months ago
Alvarez & Marsal is seeking a Senior Data Architect with a passion for data management and architecture to advance our corporate IT division. In this role, your expertise will be instrumental in the development and enhancement of our internal data warehouse and business intelligence systems, which support over 18 diverse business units. Your responsibilities will include designing, constructing, and improving our SQL data warehouse, ETL processes, and Azure environments, as well as resolving data and database issues. Success in this role requires meticulous attention to detail, proficiency with the Azure data stack, and a comprehensive understanding of data architecture principles. As a Senior Data Architect, you will develop data architecture strategies aligned with our company's goals, lead the redesign of the current SQL-based data warehouse for scalability, performance, and cost-efficiency, and design and oversee ETL development using Azure Data Factory and Informatica. You will also consolidate and standardize ETL processes using specialized tools, collaborate with ERP and other teams to review and integrate Master Data Management (MDM) requirements, and support our data governance program to ensure data quality, security, and compliance. Your role will involve utilizing Informatica for seamless data integration and management, improving existing and new subject areas within our SQL data warehouse, and maintaining high standards of data quality, consistency, and security across various sources. You will gather requirements and set data architecture standards in partnership with stakeholders, create and maintain comprehensive data models, flowcharts, and governance protocols, and promote and implement best practices for data stewardship, integration, and warehousing. Additionally, you will supervise and enhance data infrastructure for optimal performance and scalability, offer specialized knowledge on data organization, analytics, and cleansing, manage sensitive data with the highest level of discretion, and train users on new data components and data domain usage.