Senior Consultant - Data & AI Architecture
Deerfoot Recruitment Solutions
- Industry Type
- Architecture, Interior Designing
- Functional Area
- IT Industry Architecture, InteriorDesigning, AI Technology
- Nationality
- Any
- Keywords
- GCP 3 AI Solution Development 4 PoC and MVP Development 5 Business Value Delivery Strategies
Job Description
Key Responsibilities Include: 1. Designing scalable, secure, and cost-effective data architectures, analytics solutions, and AI frameworks. 2. Leading cloud transformation initiatives across AWS, Azure, and GCP environments. 3. Developing AI-enabled Proofs of Concept (PoC) and Minimum Viable Products (MVP) that deliver measurable business value. 4. Defining strategies for data management and analytics.
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About the role: Senior Consultant - Data & AI Architecture
General information about this type of role, not from the employer. The employer's actual requirements may differ, so always check the job details above.
Senior Consultants in Data & AI Architecture design and implement advanced data systems and artificial intelligence solutions to support business needs. They typically work in consulting firms, technology companies, or within the IT departments of various industries, helping organizations leverage data and AI technologies effectively.
What this role usually involves
- Develop and oversee data architecture and AI strategy aligned with business goals.
- Design scalable data models and AI frameworks for complex projects.
- Collaborate with stakeholders to understand requirements and translate them into technical solutions.
- Guide and mentor junior team members on data and AI best practices.
- Evaluate and select appropriate technologies and tools for data and AI implementations.
- Ensure data security, quality, and compliance within AI systems.
Skills employers usually look for
- Strong knowledge of data architecture and AI technologies.
- Proficiency in data modeling and machine learning concepts.
- Ability to analyze complex business problems and design technical solutions.
- Good communication and stakeholder management skills.
- Experience with cloud platforms and big data tools.
- Leadership and project management capabilities.
Usual qualifications
- A degree in computer science, information technology, or a related field.
- Professional certifications in data architecture or AI are advantageous.
- Experience with programming languages such as Python, SQL, or similar.
- Continuous learning in emerging AI and data technologies.
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