Enterprise Data Architect

Role Overview: You will be joining 66degrees as an Enterprise Data Architect, focusing on Data engineering, Data Analytics/Visualization, and cloud engineering. Your role will involve designing and overseeing enterprise-wide data solutions, leading large-scale projects, engaging in customer-facing activities, and developing data governance frameworks. Key Responsibilities: - Design and oversee enterprise-wide Data engineering, Data modeling, Data Analytics, and cloud architecture based solutions - Lead and participate in large-scale projects, integrating solutions across cloud, data engineering, Analytics practices - Engage in customer-facing roles, including presales activities and project delivery - Develop robust data governance frameworks, ensuring compliance with regulations like GDPR, CCPA, or other industry standards - Collaborate with cross-functional teams to ensure alignment of technology solutions with business objectives - Stay current with emerging technologies and industry trends, particularly in cloud computing - Build reusable assets, frameworks, and accelerators to enhance delivery efficiency - Participate in and potentially lead architectural reviews and governance processes - Contribute to the development of architectural standards, guidelines, and best practices - Travel as required, particularly to the UK, for customer engagements and project work Qualifications: - 12-15 years of total experience in IT, with a minimum of 3 years in an Enterprise Data Architect capacity - Strong expertise in data and cloud technologies, with hands-on experience in data architecture, cloud migrations, and modern data platforms - Knowledge of design patterns and architectural styles - Experience with data modeling and database design - Experience with Google Cloud Platform is a MUST, has used Google products on the data side; multi-cloud expertise is a plus - Proven track record of designing and implementing large-scale, complex systems - Familiarity with modern data tools, such as dbt, Snowflake, and Kafka, as well as proficiency in SQL and Python - Excellent communication skills, with the ability to convey complex technical concepts to both technical and non-technical audiences - Strong leadership and mentoring skills,