Walk-in || Data Architect - S

Key Responsibilities:

• Design and implement enterprise-wide data architecture strategies, frameworks, and standards.
• Develop conceptual, logical, and physical data models aligned with business requirements.
• Architect scalable data platforms, data warehouses, data lakes, and lakehouse solutions.
• Define and enforce data governance, metadata management, data quality, and master data management (MDM) practices.
• Establish data integration strategies across multiple source systems and applications.
• Collaborate with business and technical teams to understand data requirements and translate them into architecture solutions.
• Design batch and real-time data ingestion and processing frameworks.
• Ensure data security, compliance, privacy, and regulatory requirements are incorporated into architecture designs.
• Evaluate and recommend emerging technologies, tools, and best practices in data management and analytics.
• Optimize data storage, performance, scalability, and cost efficiency.
• Support cloud migration and modernization initiatives for data platforms.
• Provide technical leadership and guidance to data engineering, BI, and analytics teams.
• Develop architecture documentation, data standards, and technical roadmaps.
• Participate in solution reviews, architecture governance, and design discussions.

Required Skills & Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.

• 8+ years of experience in Data Engineering, Data Architecture, or Enterprise Data Management.

• Strong expertise in data modeling techniques including:

• Dimensional Modeling

• Data Vault

• Third Normal Form (3NF)

• Star and Snowflake Schemas

• Experience designing enterprise-scale Data Warehouses, Data Lakes, and Lakehouse architectures.

• Strong knowledge of SQL and database design principles.

• Experience with cloud data platforms such as:

• Microsoft Azure

• Amazon Web Services (AWS)

• Google Cloud Platform (GCP)

• Hands-on experience with ETL/ELT processes and data integration tools.

• Strong understanding of data governance, metadata management, and data lineage concepts.

• Experience with structured, semi-structured, and unstructured data environments.

• Excellent problem-solving, analytical, and stakeholder management skills.