Data Analytics Director

Develop and maintain the organization's data architecture, including data models, databases, and data warehouses. Design and implement a comprehensive data strategy that aligns with the organization's business objectives. Lead the organization in the identification and execution of new opportunities through data collection and insights. Plan and execute data migrations to cloud or hybrid environments, optimizing cloud-based data architectures. Design data engineering practices for efficient data management. Enhance data analysis capabilities to provide deeper insights and more accurate predictions. Evaluate specific products applicability and the scalability to handle large-scale data processing. Architect solutions that provide measurement insights into experiential marketing. Create a blueprint for data management systems to meet business and technology requirements. Coordinate with developers, database administrators, analytics team, application owners and stakeholders to establish and maintain best practices for data management. Develop executive summaries that communicate data insights and strategies to the company's leadership and stakeholders. Provide training to direct reports on the development of data engineering pipelines and data warehouses. Lead cross-functional teams across the organization to make data-driven decisions.

Requirements:

Master's degree (US or foreign equivalent) in Data Science, Business Analytics, or a related field and three (3) years of experience in the position offered or in a related role• OR Bachelor's degree (US or foreign equivalent) in Data Science, Business Analytics, or a related field and five (5) years of experience in the position offered or in a related role•All of the required experience must have included experience with: database management, SQL, and NoSQL databases; designing and structuring data to optimize storage and retrieval within databases and data warehouses; data modeling; understanding how to build and maintain data warehouses for data aggregation and analysis; building data pipelines to extract data from various sources, transform it into a usable format, and load it into target systems; utilizing tools such as Tableau and Power BI to present complex data in a visually understandable way; utilizing knowledge of machine learning concepts to build data-driven models; interpreting data and applying statistical methods to analyze trends; utilizing knowledge of cloud services such as AWS, Azure, or GCP for scalable data processing; identifying and troubleshooting complex data engineering issues; and defining project scope, timelines, and deliverables for data engineering projects. •This role entails hybrid work, with time split between working in our Detroit, MI office and flexibility to telecommute from another U.S. location.