Senior Architect - Engineering

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.

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.