Senior Architect - Engineering

Principal Financial · Pune

Responsibilities

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

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.