Lead /Principal Solution Architect (Data)

Brief Summary

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. Proven experience conducting enterprise-wide data architecture reviews. 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.