Data & Analytics Solution Architect

Tata Consultancy Services (TCS) is an equal opportunity employer, and embraces diversity in race, nationality, ethnicity, gender, age, physical ability, neurodiversity, and sexual orientation, to create a workforce that reflects the societies we operate in. Our continued commitment to Culture and Diversity is reflected in our people stories across our workforce and implemented through equitable workplace policies and processes.
Tata Consultancy Services (BSE: 532540, NSE: TCS) is the technology partner of choice for industry-leading organizations worldwide. Since its inception in 1968, TCS has upheld the highest standards of innovation, engineering excellence and customer service.
It has set an aspiration to become the world's largest AI-led technology services company and is enabling its clients to transform themselves across the full AI stack, from infrastructure to intelligence.
Rooted in the heritage of the Tata Group, TCS is focused on creating long term value for its clients, its investors, its employees, and the community h a highly skilled workforce spread across 56 countries and 194 service delivery centers across the world, the company has been recognized as a top employer in six continents. With the ability to rapidly apply and scale new technologies, the company has built long term partnerships with its clients.

Many of these relationships have endured into decades and navigated every technology cycle, from mainframes in the 1970s to artificial intelligence today.

Role Description   years of experience in Enterprise Data Architecture, AWS Data Platforms, Snowflake, Data Engineering, and Cloud Modernization.
Proven experience in Enterprise Solution architecture using AWS, Snowflake, Cortex and related technology components across the Data to Insights end to end value chain.
Strong hands-on expertise in AWS Data Services, Snowflake, Snowflake Cortex, Snowflake Horizon Catalog, Apache Iceberg / Snowflake Open Catalog, Python, PySpark, and SQL.
Proven experience designing and implementing Lakehouse Architectures, enterprise data platforms, and modern analytics solutions on AWS.
Strong understanding of the Snowflake Data Cloud, including Snowflake SQL, Workflows, Snowpipe, Snowflake Model Registry, Snowflake Horizon Catalog, Serverless Compute, and Performance Optimization.
Experience building AI-enabled analytics solutions using Snowflake Cortex, semantic models, natural language analytics, and governed data access frameworks.
Expertise in Data Engineering including ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and Data Ops practices.
Strong knowledge of Enterprise Data Architecture, including data models, data products, lakehouse and warehouse patterns, semantic layers, and master/reference data management.
Experience implementing Security, Governance, and Compliance controls including IAM/RBAC, encryption, privacy, masking, auditability, retention, and responsible AI practices.
Proven experience leading architecture definition, HLD/LLD preparation, NFR assessment, migration planning, technical governance, and production readiness activities.
Experience supporting cloud transformation initiatives, solutioning, RFP responses, effort estimation, and client-facing architecture discussions.
Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements.
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline.
Preferred certifications in AWS Solutions Architecture, Snowflake, Data Engineering, Enterprise Architecture, Security, or AI/ML
.
Engage with business and technology stakeholders to understand data, analytics, AI, and cloud transformation requirements.
Define end-to-end architecture for AWS Snowflake-based data, analytics, and AI platforms.
Design scalable, secure, and high-performance Lakehouse solutions using AWS Data Services, Snowflake, Apache Iceberg / Snowflake Open Catalog, and Snowflake Horizon Catalog.
Architect data ingestion, integration, batch, streaming, and data engineering solutions supporting enterprise analytics and AI use cases.
Design and implement AI-enabled analytics solutions using Snowflake Cortex, semantic models, and governed data access frameworks.
Establish data governance, security, metadata, lineage, observability, and responsible AI standards across the platform.
Lead data platform modernization, migration, and cloud transformation…