Role & responsibilities

Data Modelling & Architecture

Mandatory

Data Governance & Security

Mandatory

Data Warehousing & ETL/ELT Expertise

Mandatory

Cloud Architecture (AWS, Azure)

Mandatory

Snowflake Expertise

Mandatory

Preferred candidate profile

- Lead the design of enterprise data architecture including conceptual, logical, and physical models across analytical and operational domains.
- Develop, enhance, and govern data models (3NF, Dimensional, Data Vault) ensuring consistency, scalability, and alignment with enterprise standards.
- Act as the custodian of data models, defining modelling best practices, frameworks, and documentation for delivery teams.
- Design secure, governed, and compliant data environments including lineage, metadata, RBAC, data masking, and quality frameworks.
- Architect and optimize data warehousing and ELT pipelines across landing, curated, and semantic layers using modern tools and cloud-native services.
- Build and maintain cloudbased data platforms using AWS (S3, Glue, Lambda, Athena) and Azure (ADLS, ADF, Synapse) with focus on scalability, performance, and cost optimization.
- Implement and optimize Snowflake solutions including Streams, Tasks, Snowpipe, multi-cluster warehouses, micro-partitioning, and secure data sharing.
- Collaborate with engineering, product, and analytics teams to translate business requirements into robust, scalable data solutions.
- Assess new requirements, perform impact analysis, and provide estimates for model and architecture changes.




- Promote architectural alignment across teams and contribute to long-term platform and data strategy.

Technical:

- Architect and evolve enterprise data modelsspanning conceptual, logical, and physical layers—to support scalable and futureready data solutions.
- Define, standardize, and govern modelling practices (Dimensional, Data Vault, 3NF), ensuring consistent adoption across delivery and engineering teams.
- Establish secure and governed data environments by implementing robust controls for metadata, lineage, access, privacy, and data quality.
- Lead the architecture of cloudnative data pipelines and warehouse solutions, enabling effective ELT/ETL processes and reliable endtoend data flows.
- Design and optimize cloud data platforms on AWS and Azure, focusing on performance, scalability, automation, and costefficient operation.
- Develop, enhance, and finetune Snowflake implementations including warehouse strategies, pipeline components (Streams, Tasks, Snowpipe), and workload optimization.

Leadership & Collaboration:

- Provide technical leadership and mentorship to data engineers, guiding them on best practices in data modeling, architecture, cloud engineering, and Snowflake implementation.
- • Collaborate closely with data scientists, product managers, and business stakeholders to operationalize analytical and AI/ML solutions on Snowflake and AWS, ensuring alignment with enterprise architecture and strategic objectives.

📌 Data Architect (Kolkata)
🏢 Tata Consultancy Services
📍 Kolkata