- 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:

Strong 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:
Strong knowledge of modern 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 architecture and data services across AWS, Azure, or GCP.

- Data Integration:
Strong understanding of data integration patterns, APIs, batch processing, and real-time data processing.

- Security &

- Compliance:

Knowledge of data security, privacy, access controls, encryption, and compliance frameworks.

- Performance Tuning:
Ability to identify and resolve database and data pipeline performance bottlenecks.

- Analytical &

- Strategic Thinking:

Ability to understand business requirements and translate them into scalable technical and architectural solutions.

- Communication Skills:
Solid verbal and written communication skills, with the ability to explain complex architectural concepts to both technical and non-technical stakeholders.

- Architecture Tools:
Experience with data modeling and architecture tools such as ER/architecture diagramming tools.

📌 Data Architect (Mumbai)
🏢 atsMantra
📍 Mumbai