Enterprise Data Architect

GENERAL RESPONSIBILITIES

• Work with clients to understand their business needs and develop technical requirements for cloud-based data solutions.
• Design and implement logical and physical data models that are appropriate for the chosen cloud and/or hybrid data warehouse environment.
• Implement data architectures to support a variety of data formats and structures including structured, semi-structured and unstructured data.
• Participate in the definition of future data management architecture, with alignment to value creation opportunities across the business.
• Conduct complex technology and system assessments for architecture solutions
• Communicate the companywide Architecture strategy and direction to both management and systems related teams
• Stay current with new and emerging technologies and make recommendations on their adoption.
• Understand compliance and risk management requirements for supported areas
• Ensure applications adhere to established standards, policies, methodologies, and industry best practices.
• Partner with architects across Data Science and Digital organizations to create data activation frameworks supporting realtime (or near realtime) needs.

Qualifications

Position Requirements:

• Experience with multiple full life-cycle data warehouse / transformation implementations in public cloud
• Deep technical knowledge of 1 public cloud services
• 3-5 years of experience in architecting data and AI solutions on public cloud
• Deep understanding of data architectures that utilize Data Lakehouse / Data Mesh
• Demonstrated ability to quickly research, learn, adopt, and apply new technologies
• Proven experience with creating efficient (Cost/Performance) architectures that conform to functional/SLA needs
• Strong SQL and database skills working with large structured and unstructured data
• Strong familiarity with enterprise reporting solutions (PowerBI, Qlik, Tableau), data virtualization and semantic modeling
• Expertise with solution development using No-SQL data platforms
• System development lifecycle (SDLC), Agile Development, DevSecOps, and common software development tools such as Git and Jira
• Excellent written and oral communication skills to convey key choices, recommendations, and technology concepts to technical and non-technical audiences.
• Infrastructure as Code (IaC) technologies such as Azure Resource Manager (ARM) or Terraform
• Familiarity with Docker, and docker orchestration like Docker Compose or Kubernetes
• Familiarity with AI/MLOps concepts