What You'll Do Role Description: The Senior Architect - Engineering Data Science & Analytics (T7) is responsible for defining and governing enterprise-wide Data, Analytics, and AI/ML solution architectures aligned with business and technology strategies. This role drives the architecture vision for data platforms, analytics products, and cloud-based solutions while ensuring scalability, security, reliability, and performance. The incumbent partners with business collaborators, data scientists, engineering teams, product owners, and enterprise architects to deliver innovative, data-driven solutions by bringing to bear modern cloud and analytics technologies. The role also provides technical leadership, mentors teams, and drives architecture standard methodologies across the organization. Key Responsibilities:- • Have solid working understanding on Data governance concepts including data quality, data ownership/stewardship, data security and data compliance • Architecture involvement in complete data life cycle • Define and govern end-to-end solution architecture for Data, Analytics, AI/ML, and Data Platform initiatives. • Translate business and technical requirements into scalable, secure, and high-performance architecture solutions. • Develop architecture blueprints, reference architectures, roadmaps, and solution design artifacts. • Lead architecture reviews, design governance, technology evaluations, and PoCs. • Design enterprise data platforms, data lakes, data warehouses, and cloud-based analytics solutions. • Establish data architecture standards, data models, integration patterns, governance, and data quality frameworks. • Provide architectural leadership for Data Science, Machine Learning, and MLOps platforms. • Partner with Data Scientists, Engineering teams, and business collaborators to deliver advanced analytics and technology-based solutions. • Drive adoption of Snowflake, AWS, modern data products, and analytics technologies. • Mentor architects and technical teams, promoting architecture guidelines and technical perfection. • Identify architectural risks, dependencies, and mitigation strategies to ensure successful delivery. • Collaborate with business, product, and delivery teams to define technology roadmaps and transformation initiatives. • Present architecture recommendations to senior leadership and governance forums. • Ensure alignment with SDLC, security, compliance, and architecture governance standards. • Support estimation, planning, technical decision-making, and continuous improvement initiatives. Who You Are Qualifications: • Bachelor’s degree or equivalent experience in computer science, Information Technology, Engineering, Data Science, or related field. • 13-15 years of overall experience in technology with significant experience in Solution Architecture, Data Architecture, and Analytics platforms. • Proven experience designing and implementing enterprise-scale Data & Analytics solutions. • Experience leading multi-functional teams and large-scale transformation initiatives. • Strong understanding of Agile, SAFe, DevOps, and modern software delivery methodologies. Must Have Skills: • Solution Architecture / Enterprise Architecture • Data Architecture & Analytics Architecture • Data Science & Machine Learning Platforms • Snowflake Architecture and Data Cloud • AWS Cloud Services & Cloud Architecture • Data Warehousing, Data Lakes, and Lakehouse Architectures • Data Modeling, Data Integration, and Data Governance • MLOps and AI/ML Solution Design • Business Intelligence Tools (Power BI, Tableau, Looker or equivalent) • Architecture Governance and Design Reviews • Partner Management and Executive Communication • Technical Leadership, Mentoring, and Team Development • Strong analytical, problem-solving, and solutioning skills Other: • • Ability to influence architecture decisions across multiple programs and teams. • Strong customer-centric approach with excellent communication and presentation skills. • Experience in conducting architecture assessments, POCs, and reference implementations. • Ability to balance business, technology, security, scalability, and operational considerations. • Awareness of emerging trends in Data, Analytics, AI/ML, Cloud, and Modern Data Platforms. • Dedicated to investigation with a passion for innovation and continuous learning. • Strong decision-making, conflict resolution, and collaborator engagement capabilities. • Experience working in global, matrixed, and enterprise environments preferred.