Enterprise Cloud Data Architect

2 weeks ago

Ann Arbor, United States Evolutyz Corp Full time

Position is eligible for 10% bonus. Onsite presence 2-3 days per week is REQUIRED.

As a Cloud Data Solutions Architect focused on Data Solutions and Data Management, your primary responsibility will be to ensure building a scalable, secure and efficient data platform / lakehouse with Azure / Databricks. The role is a senior level technical role that will be accountable for the end-to-end cloud data management solution. The ideal candidate will have experience in large scale modern data warehouse development and had success leading cross-team technical discussions that drive key decisions and implementation. The cloud data solutions architect would partner with Digital/AI/ML Architects and teams to define data activation frameworks.
Role: Hybrid (at Client Headquarters, Ann Arbor)
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 / governance 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 Client 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

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