Principal Data Architect The Principle Data Architect is responsible leading the design, implementation, and evolution of our enterprise data architecture. This role plays a strategic role in ensuring the Park Place data ecosystem supports current and future business objectives, enabling advanced analytics, operational efficiency, and scalability. What you’ll be doing: · Define and maintain the enterprise data architecture vision, strategy, and roadmap, including data modeling, data integration, data warehousing, and business intelligence. · Lead the design and implementation of complex data solutions, including data pipelines, data lakes, and data warehouses, ensuring scalability, performance, and security. · Evaluate and recommend new and emerging data technologies, tools, and techniques to support business needs and drive innovation. · Collaborate with stakeholders to establish and enforce data governance policies, standards, and procedures to ensure data quality, integrity, and compliance. · Provide technical leadership and mentorship to data architects, engineers, and analysts, fostering a culture of collaboration and knowledge sharing. · Effectively communicate and collaborate with business stakeholders, IT leaders, and project teams to understand data requirements and deliver solutions that meet their needs. · Stay abreast of industry trends and best practices in data architecture, data management, and data security. · Develop and maintain comprehensive documentation of data architecture artifacts, including data models, data flow diagrams, and data dictionaries. · Other duties as assigned. What we’re looking for: · 10+ years of experience in data architecture, data warehousing, or related fields, with a proven track record of designing and implementing complex data solutions. · Deep understanding of data modeling techniques (e.g., relational, dimensional, NoSQL), data integration patterns (e.g., ETL, ELT), and data warehousing principles. · Experience with cloud-based data platforms (e.g., Azure, GCP, AWS) and data lake technologies. · Strong understanding of data governance principles, data quality management, and data security best practices. · Excellent communication, interpersonal, and leadership skills with the ability to influence and collaborate effectively with diverse stakeholders. · Strong analytical and problem-solving skills with a proven ability to identify and resolve complex data challenges. · Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. Bonus Points: · Experience with data visualization tools and techniques. · Knowledge of data science and machine learning concepts. · Experience with Agile methodologies. · Relevant certifications (e.g., Azure Solutions Architect) Education: · Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. Travel: • <10%