Lead Data Architecture Consultant

About

Join our dynamic team as a Lead Data Architecture Consultant, where you will play a crucial role in guiding our digital transformation journey towards becoming an AI-enabled enterprise. This position offers an exciting opportunity to shape data strategies and frameworks that drive innovation across the organization.

Responsibilities

• Serve as the primary consultant for data architecture, delivering strategic guidance across various teams.
• Review existing system data architectures to ensure they align with the enterprise’s AI roadmap.
• Drive standardization initiatives for seamless integration and intelligent capabilities.
• Collaborate with business stakeholders, technology vendors, and cross-functional teams to assess current data landscapes and identify transformation opportunities.
• Establish architectural principles that facilitate the adoption of advanced analytics, machine learning, and artificial intelligence.
• Develop enterprise-wide data strategies and governance frameworks, promoting best practices for AI readiness.

Requirements

• Degree in Computer Engineering, Computer Science, Data Science, or a related technical field.
• Minimum of 8 years of experience in enterprise data architecture consulting, demonstrating the ability to assess and align diverse system architectures.
• Strong understanding of enterprise architecture frameworks and methodologies for large-scale system integration.
• Advanced proficiency in evaluating and standardizing data architectures across cloud platforms (AWS, Microsoft Azure, Google Cloud Platform).
• Familiarity with architectural assessment tools and frameworks for analyzing enterprise data landscapes.
• Hands-on experience with various data technologies, including relational databases (PostgreSQL, MySQL, SQL Server), NoSQL databases (MongoDB, Cassandra), and in-memory databases (Redis).
• Understanding of AI/ML architectural patterns, data pipeline designs, and requirements for integrating intelligent systems.
• Experience in establishing enterprise-wide data standards and governance policies.
• Strong analytical skills to evaluate complex, heterogeneous data environments and influence architectural decisions across multiple business units and technology teams.