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.

·       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.

·       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.

·       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)

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

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