Data Modeling & Design:
Design and develop logical and physical data models, including database schemas, blueprints, and architecture diagrams.
Data Architecture:
Define scalable data architecture frameworks covering data collection, storage, processing, integration, and consumption.
Infrastructure Planning:
Design and implement data warehouses, data lakes, ETL/ELT pipelines, and data integration solutions.
Security & Compliance:
Ensure data platforms comply with regulatory and organizational standards such as GDPR, HIPAA, and other data privacy requirements.
Performance Optimization:
Monitor, analyze, and optimize database and data platform performance to efficiently handle large-scale data volumes.
Data Governance:
Establish standards for data quality, security, metadata management, accessibility, and lifecycle management.
Technology Strategy:
Evaluate data technologies and recommend scalable, cost-effective solutions aligned with enterprise requirements.
Strategic Collaboration:
Work closely with business stakeholders, data engineers, developers,



and technical teams to align data architecture with business objectives.
Architecture Documentation:
Create and maintain architecture diagrams, technical specifications, data models, and design documentation.
Problem Solving:
Identify data architecture challenges and implement robust solutions to improve reliability, scalability, and maintainability.

Essential Skills
Data Architecture & Modeling:
Robust expertise in data modeling, database architecture, logical and physical data models, and schema design.
Database Technologies:
Hands-on experience with SQL and relational database management systems (RDBMS).
Data Warehousing:
Robust knowledge of up-to-date data warehouse technologies such as
Snowflake, Amazon Redshift
, or equivalent platforms.
ETL/ELT:
Experience designing and implementing ETL/ELT processes and enterprise data pipelines.
Cloud Data Platforms:
Understanding of cloud-based data a

📌 Data Architect Mumbai (India)
🏢 atsMantra
📍 India